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Guofu Zhou

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    2. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    3. Massacci, Daniele & Kapetanios, George, 2024. "Forecasting in factor augmented regressions under structural change," International Journal of Forecasting, Elsevier, vol. 40(1), pages 62-76.
    4. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    5. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    6. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    7. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    8. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    9. Yingying Xu & Jichang Zhao, 2022. "Can sentiments on macroeconomic news explain stock returns? Evidence form social network data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2073-2088, April.
    10. Libo Yin & Qingyuan Yang & Zhi Su, 2017. "Predictability of structural co-movement in commodity prices: the role of technical indicators," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 795-812, May.
    11. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    12. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    13. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    14. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    15. Chen, Kuan-Hau & Su, Xuan-Qi & Lin, Li-Feng & Shih, Yi-Cheng, 2021. "Profitability of moving-average technical analysis over the firm life cycle: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    16. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2021. "Persistence in the market risk premium: evidence across countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(3), pages 413-427, July.
    17. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    18. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Econometric Institute Research Papers EI2018-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022. "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    20. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    21. Tsiakas, Ilias & Zhang, Haibin, 2021. "Economic fundamentals and the long-run correlation between exchange rates and commodities," Global Finance Journal, Elsevier, vol. 49(C).
    22. Eom, Cheoljun & Park, Jong Won, 2023. "Price behavior of small-cap stocks and momentum: A study using principal component momentum," Research in International Business and Finance, Elsevier, vol. 65(C).
    23. Smith, Simon C., 2017. "Equity premium estimates from economic fundamentals under structural breaks," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 49-61.
    24. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    25. Scholz, Michael & Nielsen, Jens Perch & Sperlich, Stefan, 2015. "Nonparametric prediction of stock returns based on yearly data: The long-term view," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 143-155.
    26. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting rare earth stock prices with machine learning," Resources Policy, Elsevier, vol. 86(PA).
    27. Ikhlaas Gurrib & Mohammad Nourani & Rajesh Kumar Bhaskaran, 2022. "Energy crypto currencies and leading U.S. energy stock prices: are Fibonacci retracements profitable?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-27, December.
    28. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    29. Qingxiang Han & Mengxi He & Yaojie Zhang & Muhammad Umar, 2023. "Default return spread: A powerful predictor of crude oil price returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1786-1804, November.
    30. Fernando M. Duarte & Carlo Rosa, 2015. "The equity risk premium: a review of models," Economic Policy Review, Federal Reserve Bank of New York, issue 2, pages 39-57.
    31. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
    32. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    33. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    34. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    35. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    36. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    37. Yaojie Zhang & Qingxiang Han & Mengxi He, 2024. "Forecasting stock market returns with a lottery index: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1595-1606, August.
    38. Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
    39. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    40. Ma, Feng & Lu, Fei & Tao, Ying, 2022. "Geopolitical risk and excess stock returns predictability: New evidence from a century of data," Finance Research Letters, Elsevier, vol. 50(C).
    41. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    42. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    43. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    44. Lyu, Zhichong & Ma, Feng & Zhang, Jixiang, 2023. "Oil futures volatility prediction: Bagging or combination?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 457-467.
    45. Shi, Qi & Li, Bin, 2022. "Further evidence on financial information and economic activity forecasts in the United States," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    46. Mei, Dexiang & Zeng, Qing & Zhang, Yaojie & Hou, Wenjing, 2018. "Does US Economic Policy Uncertainty matter for European stock markets volatility?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 215-221.
    47. Kenechukwu E. Anadu & James Bohn & Lina Lu & Matthew Pritsker & Andrei Zlate, 2019. "Reach for Yield by U.S. Public Pension Funds," Finance and Economics Discussion Series 2019-048, Board of Governors of the Federal Reserve System (U.S.).
    48. Yin, Libo & Su, Zhi & Lu, Man, 2022. "Is oil risk important for commodity-related currency returns?," Research in International Business and Finance, Elsevier, vol. 60(C).
    49. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    50. Xu, Yongan & Liang, Chao & Wang, Jianqiong, 2023. "Financial stress and returns predictability: Fresh evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    51. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    52. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Business School, revised Feb 2018.
    53. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    54. Taylor, Mark & Hsu, Po-Hsuan & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
    55. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    56. Matthew Lorig & Zhou Zhou & Bin Zou, 2017. "A Mathematical Analysis of Technical Analysis," Papers 1710.09476, arXiv.org, revised Feb 2019.
    57. Mingwei Sun & Paskalis Glabadanidis, 2022. "Can technical indicators predict the Chinese equity risk premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 114-142, March.
    58. Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2013. "Can Economic Uncertainty, Financial Stress and Consumer Sentiments Predict U.S. Equity Premium?," Working Papers 201351, University of Pretoria, Department of Economics.
    59. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    60. Jurdi, Doureige & Kim, Jae, 2019. "Predicting the U.S. Stock Market Return: Evidence from the Improved Augmented Regression Method," MPRA Paper 94028, University Library of Munich, Germany.
    61. Dai, Zhifeng & Zhou, Huiting & Wen, Fenghua & He, Shaoyi, 2020. "Efficient predictability of stock return volatility: The role of stock market implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    62. Zarrabi, Nima & Snaith, Stuart & Coakley, Jerry, 2017. "FX technical trading rules can be profitable sometimes!," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 113-127.
    63. Tzeng, Kae-Yih & Su, Yi-Kai, 2024. "Can U.S. macroeconomic indicators forecast cryptocurrency volatility?," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    64. Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024. "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper 122899, University Library of Munich, Germany.
    65. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    66. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "Asymmetric Risk Impacts of Chinese Tourists to Taiwan," Tinbergen Institute Discussion Papers 18-047/III, Tinbergen Institute.
    67. Caginalp, Gunduz & DeSantis, Mark, 2020. "Nonlinear price dynamics of S&P 100 stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    68. Apergis, Nicholas & Gupta, Rangan, 2017. "Can (unusual) weather conditions in New York predict South African stock returns?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 377-386.
    69. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    70. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    71. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    72. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    73. Aladesanmi, Olalekan & Casalin, Fabrizio & Metcalf, Hugh, 2019. "Stock market integration between the UK and the US: Evidence over eight decades," Global Finance Journal, Elsevier, vol. 41(C), pages 32-43.
    74. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    75. Vecchi, Edoardo & Berra, Gabriele & Albrecht, Steffen & Gagliardini, Patrick & Horenko, Illia, 2023. "Entropic approximate learning for financial decision-making in the small data regime," Research in International Business and Finance, Elsevier, vol. 65(C).
    76. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
    77. Zhang, Dan & Li, Biangxiang, 2022. "What can we learn from financial stress indicator?," Finance Research Letters, Elsevier, vol. 50(C).
    78. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    79. Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
    80. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    81. Lv, Wendai & Qi, Jipeng, 2022. "Stock market return predictability: A combination forecast perspective," International Review of Financial Analysis, Elsevier, vol. 84(C).
    82. Dat Thanh Tran & Alexandros Iosifidis & Juho Kanniainen & Moncef Gabbouj, 2017. "Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis," Papers 1712.00975, arXiv.org.
    83. Luo, Jiawen & Klein, Tony & Walther, Thomas & Ji, Qiang, 2021. "Forecasting Realized Volatility of Crude Oil Futures Prices based on Machine Learning," QBS Working Paper Series 2021/04, Queen's University Belfast, Queen's Business School.
    84. Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023. "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, vol. 125(C).
    85. Lu, Fei & Ma, Feng, 2023. "Cross-sectional uncertainty and stock market volatility: New evidence," Finance Research Letters, Elsevier, vol. 57(C).
    86. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    87. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    88. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
    89. Xianfeng Hao & Yudong Wang, 2023. "Forecasting the stock risk premium: A new statistical constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1805-1822, November.
    90. Lee, Hsiu-Chuan & Lee, Yun-Huan & Nguyen, Cuong, 2023. "Tail comovements of implied volatility indices and global index futures returns predictability," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    91. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    92. GONÇALVES, Sílvia & PERRON, Benoit, 2018. "Bootstrapping factor models with cross sectional dependence," Cahiers de recherche 2018-07, Universite de Montreal, Departement de sciences economiques.
    93. Haibin Xie & Shouyang Wang, 2015. "Risk-return trade-off, information diffusion, and U.S. stock market predictability," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-20, December.
    94. Xiaojun Chu & Jianying Qiu, 2021. "Forecasting stock returns using first half an hour order imbalance," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3236-3245, July.
    95. Xianzheng Zhou & Hui Zhou & Huaigang Long, 2023. "Forecasting the equity premium: Do deep neural network models work?," Modern Finance, Modern Finance Institute, vol. 1(1), pages 1-11.
    96. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    97. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    98. Liu, Zhichao & Liu, Jing & Zeng, Qing & Wu, Lan, 2022. "VIX and stock market volatility predictability: A new approach," Finance Research Letters, Elsevier, vol. 48(C).
    99. Weijia Peng & Chun Yao, 2023. "Sector-level equity returns predictability with machine learning and market contagion measure," Empirical Economics, Springer, vol. 65(4), pages 1761-1798, October.
    100. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    101. Baetje, Fabian & Menkhoff, Lukas, 2013. "Macro determinants of U.S. stock market risk premia in bull and bear markets," Hannover Economic Papers (HEP) dp-520, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    102. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    103. Panpan Zhu & Xing Zhang & You Wu & Hao Zheng & Yinpeng Zhang, 2021. "Investor attention and cryptocurrency: Evidence from the Bitcoin market," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-28, February.
    104. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    105. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2023. "Forecasting crude oil prices: A reduced-rank approach," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 698-711.
    106. Ikhlaas Gurrib & Firuz Kamalov & Elgilani Elshareif, 2021. "Can the Leading US Energy Stock Prices be Predicted using the Ichimoku Cloud?," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 41-51.
    107. Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
    108. Li, Zhiyong & Wan, Yifan & Wang, Tianyi & Yu, Mei, 2023. "Factor-timing in the Chinese factor zoo: The role of economic policy uncertainty," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    109. Charles, Amelie & Darne, Olivier & Kim, Jae, 2016. "Stock Return Predictability: Evaluation based on Prediction Intervals," MPRA Paper 70143, University Library of Munich, Germany.
    110. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market Instability and Technical Trading at High Frequency: Evidence from NASDAQ Stocks," LIDAM Reprints LFIN 2021016, Université catholique de Louvain, Louvain Finance (LFIN).
    111. Xu, Yanyan & Liu, Jing & Ma, Feng & Chu, Jielei, 2024. "Liquidity and realized volatility prediction in Chinese stock market: A time-varying transitional dynamic perspective," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 543-560.
    112. Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    113. Fong, Tom Pak Wing & Wu, Shui Tang, 2020. "Predictability in sovereign bond returns using technical trading rules: Do developed and emerging markets differ?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    114. José Afonso Faias & Juan Arismendi Zambrano, 2022. "Equity Risk Premium Predictability from Cross-Sectoral Downturns [International asset allocation with regime shifts]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 808-842.
    115. Hoang, Lai T. & Baur, Dirk G., 2022. "Loaded for bear: Bitcoin private wallets, exchange reserves and prices," Journal of Banking & Finance, Elsevier, vol. 144(C).
    116. Luo, Keyu & Guo, Qiang & Li, Xiafei, 2022. "Can the return connectedness indices from grey energy to natural gas help to forecast the natural gas returns?," Energy Economics, Elsevier, vol. 109(C).
    117. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    118. Felix Haase, 2024. "Sum-of-the-Parts Revised: Economic Regimes and Flexible Probabilities," Research Papers in Economics 2024-10, University of Trier, Department of Economics.
    119. Geng, Qianjie & Wang, Yudong, 2024. "Forecasting the volatility of crude oil basis: Univariate models versus multivariate models," Energy, Elsevier, vol. 295(C).
    120. Huadong Chang & Guozhi An, 2019. "Will History Repeat Itself? Empirical Research on A-Share Candlesticks in China Based on Matching Method," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(5), pages 1-8.
    121. Noureddine Kouaissah & Amin Hocine, 2021. "Forecasting systemic risk in portfolio selection: The role of technical trading rules," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 708-729, July.
    122. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    123. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    124. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    125. Cao, Sean & Jiang, Wei & Wang, Junbo & Yang, Baozhong, 2024. "From Man vs. Machine to Man + Machine: The art and AI of stock analyses," Journal of Financial Economics, Elsevier, vol. 160(C).
    126. Massoud Metghalchi & Linda A. Hayes & Farhang Niroomand, 2019. "A technical approach to equity investing in emerging markets," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 389-403, July.
    127. Huang, Jing-Zhi & Huang, Zhijian (James), 2020. "Testing moving average trading strategies on ETFs," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 16-32.
    128. Antonios K. Alexandridis & Ekaterini Panopoulou & Ioannis Souropanis, 2024. "Forecasting exchange rates: An iterated combination constrained predictor approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 983-1017, July.
    129. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    130. Ma, Feng & Wu, Hanlin & Zeng, Qing, 2024. "Biodiversity and stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    131. Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
    132. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
    133. Keith S. K. Lam & Liang Dong & Bo Yu, 2019. "Value Premium and Technical Analysis: Evidence from the China Stock Market," Economies, MDPI, vol. 7(3), pages 1-21, September.
    134. Gu, Ming & Sun, Minxing & Xiong, Zhitao & Xu, Weike, 2024. "Market volatility and the trend factor," Finance Research Letters, Elsevier, vol. 65(C).
    135. Mengxi He & Yaojie Zhang & Yudong Wang & Danyan Wen, 2024. "Modelling and forecasting crude oil price volatility with climate policy uncertainty," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    136. Davide Pettenuzzo & Allan Timmermann & Rossen Valkanov, 2013. "Forecasting Stock Returns under Economic Constraints," Working Papers 57, Brandeis University, Department of Economics and International Business School.
    137. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
    138. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    139. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    140. Viet Anh Nguyen & Fan Zhang & Shanshan Wang & Jose Blanchet & Erick Delage & Yinyu Ye, 2021. "Robustifying Conditional Portfolio Decisions via Optimal Transport," Papers 2103.16451, arXiv.org, revised Apr 2024.
    141. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Long, Jian-You & Zhou, Yang, 2023. "Forecasting stock market volatility under parameter and model uncertainty," Research in International Business and Finance, Elsevier, vol. 66(C).
    142. Zhang, Junting & Liu, Haifei & Bai, Wei & Li, Xiaojing, 2024. "A hybrid approach of wavelet transform, ARIMA and LSTM model for the share price index futures forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    143. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    144. Chaonan Lin & Nien‐Tzu Yang & Robin K. Chou & Kuan‐Cheng Ko, 2022. "A timing momentum strategy," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1339-1379, April.
    145. Gerritsen, Dirk F. & Bouri, Elie & Ramezanifar, Ehsan & Roubaud, David, 2020. "The profitability of technical trading rules in the Bitcoin market," Finance Research Letters, Elsevier, vol. 34(C).
    146. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
    147. Adrian Zoicas‐Ienciu, 2021. "Evaluating active investing with generic trading reactions," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1018-1036, January.
    148. Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
    149. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    150. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    151. Yamani, Ehab, 2023. "The informational role of fund flow in the profitable predictability of mutual funds," Finance Research Letters, Elsevier, vol. 51(C).
    152. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    153. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    154. Kartikay Gupta & Niladri Chatterjee, 2021. "Stocks Recommendation from Large Datasets Using Important Company and Economic Indicators," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 667-689, December.
    155. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    156. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
    157. Fameliti Stavroula & Skintzi Vasiliki, 2024. "Macroeconomic attention and commodity market volatility," Empirical Economics, Springer, vol. 67(5), pages 1967-2007, November.
    158. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
    159. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    160. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    161. Zhao, Dongxu & Li, Kai, 2022. "Bounded rationality, adaptive behaviour, and asset prices," International Review of Financial Analysis, Elsevier, vol. 80(C).
    162. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    163. Ma, Chenyao & Yan, Sheng, 2022. "Deep learning in the Chinese stock market: The role of technical indicators," Finance Research Letters, Elsevier, vol. 49(C).
    164. Demir Bektić & Tobias Regele, 2018. "Exploiting uncertainty with market timing in corporate bond markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 79-92, March.
    165. Paskalis Glabadanidis, 2014. "The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes," International Review of Finance, International Review of Finance Ltd., vol. 14(2), pages 161-202, June.
    166. Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
    167. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    168. Yun‐Huan Lee & Tzu‐Hsiang Liao & Hsiu‐Chuan Lee, 2022. "Overnight returns of industry exchange‐traded funds, investor sentiment, and futures market returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1114-1134, June.
    169. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Market Timing with Moving Averages for Fossil Fuel and Renewable Energy Stocks," Econometric Institute Research Papers EI2018-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    170. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    171. Ma, Yao & Yang, Baochen & Li, Jinyong & Shen, Yue, 2023. "Trend information and cross-sectional returns: The role of analysts," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    172. Bley, Jorg & Saad, Mohsen, 2020. "An analysis of technical trading rules: The case of MENA markets," Finance Research Letters, Elsevier, vol. 33(C).
    173. Gunduz Caginalp & Mark DeSantis, 2019. "Nonlinear price dynamics of S&P 100 stocks," Papers 1907.04422, arXiv.org.
    174. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    175. Kentaro Imajo & Kentaro Minami & Katsuya Ito & Kei Nakagawa, 2020. "Deep Portfolio Optimization via Distributional Prediction of Residual Factors," Papers 2012.07245, arXiv.org.
    176. Syed Abul, Basher & Perry, Sadorsky, 2022. "Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?," MPRA Paper 113293, University Library of Munich, Germany.
    177. Liu, Li & Ma, Feng & Wang, Yudong, 2015. "Forecasting excess stock returns with crude oil market data," Energy Economics, Elsevier, vol. 48(C), pages 316-324.
    178. Algaba, Andres & Boudt, Kris, 2017. "Generalized financial ratios to predict the equity premium," Economic Modelling, Elsevier, vol. 66(C), pages 244-257.
    179. Massimo Guidolin & Erwin Hansen & Gabriel Cabrera, 2023. "Time-Varying Risk Aversion and International Stock Returns," BAFFI CAREFIN Working Papers 23203, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    180. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    181. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    182. Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
    183. Yuan, Xianghui & Li, Xiang, 2022. "Delta-hedging demand and intraday momentum: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    184. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    185. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    186. Calice, Giovanni & Lin, Ming-Tsung, 2021. "Exploring risk premium factors for country equity returns," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 294-322.
    187. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    188. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    189. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.
    190. Nuno Silva, 2013. "Equity Premia Predictability in the EuroZone," GEMF Working Papers 2013-22, GEMF, Faculty of Economics, University of Coimbra.
    191. Lin, Qi & Lin, Xi, 2021. "Are the profitability and investment factors valid ICAPM risk factors? Pre-1963 evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    192. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
    193. Yamani, Ehab, 2021. "Foreign exchange market efficiency and the global financial crisis: Fundamental versus technical information," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 74-89.
    194. Barua, Ronil & Sharma, Anil K., 2023. "Using fear, greed and machine learning for optimizing global portfolios: A Black-Litterman approach," Finance Research Letters, Elsevier, vol. 58(PC).
    195. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    196. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    197. Oguzhan Cepni & Rangan Gupta & I. Ethem Guney & M. Hasan Yilmaz, 2019. "Forecasting Local Currency Bond Risk Premia of Emerging Markets: The Role of Cross-Country Macro-Financial Linkages," Working Papers 201957, University of Pretoria, Department of Economics.
    198. Hong, KiHoon & Wu, Eliza, 2016. "The roles of past returns and firm fundamentals in driving US stock price movements," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 62-75.
    199. Yamani, Ehab, 2021. "Can technical trading beat the foreign exchange market in times of crisis?," Global Finance Journal, Elsevier, vol. 48(C).
    200. Lim, Bryan Y. & Wang, Jiaguo (George) & Yao, Yaqiong, 2018. "Time-series momentum in nearly 100 years of stock returns," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 283-296.
    201. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    202. Fei Lu & Feng Ma & Elie Bouri, 2024. "Stock market volatility predictability: new evidence from energy consumption," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    203. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.
    204. Chung, Chien-Ping & Chien, Cheng-Yi & Huang, Chia-Hsin & Lee, Hsiu-Chuan, 2021. "Foreign institutional ownership and the effectiveness of technical analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 86-96.
    205. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    206. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    207. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    208. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2017. "Time series momentum and moving average trading rules," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 405-421, March.
    209. Ma, Yao & Yang, Baochen & Su, Yunpeng, 2021. "Stock return predictability: Evidence from moving averages of trading volume," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    210. Harvey, David I & Leybourne, Stephen J & Sollis, Robert & Taylor, AM Robert, 2020. "Real-Time Detection of Regimes of Predictability in the U.S. Equity Premium," Essex Finance Centre Working Papers 27775, University of Essex, Essex Business School.
    211. Xiaoxi Liu & Jinming Xie, 2023. "Forecasting swap rate volatility with information from swaptions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 455-479, April.
    212. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    213. Faria, Gonçalo & Verona, Fabio, 2024. "Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators," Bank of Finland Research Discussion Papers 14/2024, Bank of Finland.
    214. Qiu, Rui & Liu, Jing & Li, Yan, 2023. "Long-term adjusted volatility: Powerful capability in forecasting stock market returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    215. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    216. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
    217. Shu‐Lien Chang & Hsiu‐Chuan Lee & Donald Lien, 2022. "The global latent factor and international index futures returns predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 514-538, April.
    218. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    219. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
    220. Ali Al-Ameer & Khaled Alshehri, 2021. "Conditional Value-at-Risk for Quantitative Trading: A Direct Reinforcement Learning Approach," Papers 2109.14438, arXiv.org.
    221. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    222. Hubert Dichtl & Wolfgang Drobetz & Viktoria‐Sophie Wendt, 2021. "How to build a factor portfolio: Does the allocation strategy matter?," European Financial Management, European Financial Management Association, vol. 27(1), pages 20-58, January.
    223. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    224. Becker, Janis & Leschinski, Christian, 2018. "Directional Predictability of Daily Stock Returns," Hannover Economic Papers (HEP) dp-624, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    225. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    226. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Forecasting the CNY-CNH pricing differential: The role of investor attention," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 232-247.
    227. Li, Dakai, 2024. "Forecasting stock market realized volatility: The role of investor attention to the price of petroleum products," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 115-122.
    228. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    229. Zhifeng Dai & Jie Kang & Hua Yin, 2023. "Forecasting equity risk premium: A new method based on wavelet de‐noising," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4331-4352, October.
    230. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    231. Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.
    232. Dai, Zhifeng & Zhou, Huiting & Kang, Jie & Wen, Fenghua, 2021. "The skewness of oil price returns and equity premium predictability," Energy Economics, Elsevier, vol. 94(C).
    233. N. Banholzer & S. Heiden & D. Schneller, 2019. "Exploiting investor sentiment for portfolio optimization," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 671-702, December.
    234. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    235. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    236. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    237. Yongsheng Yi & Feng Ma & Dengshi Huang & Yaojie Zhang, 2019. "Interest rate level and stock return predictability," Review of Financial Economics, John Wiley & Sons, vol. 37(4), pages 506-522, October.
    238. Wang, Yuejing & Ye, Wuyi & Jiang, Ying & Liu, Xiaoquan, 2024. "Volatility prediction for the energy sector with economic determinants: Evidence from a hybrid model," International Review of Financial Analysis, Elsevier, vol. 92(C).
    239. Ma, Yao & Yang, Baochen & Su, Yunpeng, 2020. "Technical trading index, return predictability and idiosyncratic volatility," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 879-900.
    240. Ni, Yensen & Cheng, Yirung & Huang, Paoyu & Day, Min-Yuh, 2018. "Trading strategies in terms of continuous rising (falling) prices or continuous bullish (bearish) candlesticks emitted," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 188-204.
    241. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
    242. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    243. Liu, Jing & He, Qiubei & Li, Yan & Huynh, Luu Duc Toan & Liang, Chao, 2023. "The change in stock-selection risk and stock market returns," International Review of Financial Analysis, Elsevier, vol. 85(C).
    244. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    245. Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Simple Market Timing with Moving Averages," Econometric Institute Research Papers EI2018-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    246. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    247. Dai, Zhifeng & Zhu, Huan & Kang, Jie, 2021. "New technical indicators and stock returns predictability," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 127-142.
    248. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    249. Li Liu & Yudong Wang, 2021. "Forecasting aggregate market volatility: The role of good and bad uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 40-61, January.
    250. Sang Il Lee, 2020. "Deeply Equal-Weighted Subset Portfolios," Papers 2006.14402, arXiv.org.
    251. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    252. Karabiyik, Hande & Westerlund, Joakim & Narayan, Paresh, 2016. "On the estimation and testing of predictive panel regressions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 115-125.
    253. Cakici, Nusret & Zaremba, Adam & Bianchi, Robert J. & Pham, Nga, 2021. "False discoveries in the anomaly research: New insights from the Stock Exchange of Melbourne (1927–1987)," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    254. Dai, Zhifeng & Zhang, Xiaotong & Liang, Chao, 2024. "Efficient predictability of oil price: The role of VIX-based panic index shadow line difference," Energy Economics, Elsevier, vol. 129(C).
    255. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).
    256. Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
    257. Yufeng Han & Dayong Huang & Guofu Zhou, 2021. "Anomalies enhanced: A portfolio rebalancing approach," Financial Management, Financial Management Association International, vol. 50(2), pages 371-424, June.
    258. De Simone, Francisco Nadal, 2024. "The transmission of U.S. monetary policy to small open economies," Journal of International Money and Finance, Elsevier, vol. 142(C).
    259. Goodness C. Aye & Rangan Gupta & Mampho P. Modise, 2012. "Structural Breaks and Predictive Regressions Models of South African Equity Premium," Working Papers 201209, University of Pretoria, Department of Economics.
    260. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
    261. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.
    262. Li, Chenchen & Wang, Yudong & Wu, Chongfeng, 2022. "Oil implied volatility and expected stock returns along the worldwide supply chain," Energy Economics, Elsevier, vol. 114(C).
    263. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    264. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    265. Ding Du & Ronald J Gunderson & Xiaobing Zhao, 2016. "Investor sentiment and oil prices," Journal of Asset Management, Palgrave Macmillan, vol. 17(2), pages 73-88, March.
    266. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    267. Lu Wang & Feng Ma & Guoshan Liu & Qiaoqi Lang, 2023. "Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2056-2073, April.
    268. Kenan Qiao & Haibin Xie, 2024. "Time‐varying risk preference and equity risk premium forecasting: The role of the disposition effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2659-2674, November.
    269. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Multi-factor volatility and stock returns," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 132-149.
    270. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    271. David E. Rapach & Matthew C. Ringgenberg & Guofu Zhou, 2016. "Short interest and aggregate stock returns," CEMA Working Papers 716, China Economics and Management Academy, Central University of Finance and Economics.
    272. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
    273. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    274. Nuno Silva, 2015. "Time-Varying Stock Return Predictability: The Eurozone Case," Notas Económicas, Faculty of Economics, University of Coimbra, issue 41, pages 28-38, June.
    275. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    276. Ma, Feng & Cao, Jiawei, 2023. "The Chinese equity premium predictability: Evidence from a long historical data," Finance Research Letters, Elsevier, vol. 53(C).
    277. Robert Czudaj, 2019. "Crude oil futures trading and uncertainty," Chemnitz Economic Papers 027, Department of Economics, Chemnitz University of Technology, revised Jan 2019.
    278. Paskalis Glabadanidis, 2015. "Market Timing With Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 387-425, September.
    279. Liu, Jingzhen, 2019. "Impacts of lagged returns on the risk-return relationship of Chinese aggregate stock market: Evidence from different data frequencies," Research in International Business and Finance, Elsevier, vol. 48(C), pages 243-257.
    280. Thorsten Lehnert & Gildas Blanchard & Dennis Bams, 2014. "Evaluating Option Pricing Model Performance Using Model Uncertainty," LSF Research Working Paper Series 14-06, Luxembourg School of Finance, University of Luxembourg.
    281. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    282. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    283. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    284. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    285. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    286. Qian, Lihua & Zeng, Qing & Li, Tao, 2022. "Geopolitical risk and oil price volatility: Evidence from Markov-switching model," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 29-38.
    287. Li, Hongchang & Strauss, Jack & Shunxiang, Hu & Lui, Lu, 2018. "Do high-speed railways lead to urban economic growth in China? A panel data study of China’s cities," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 70-89.
    288. Yu, Jing-Rung & Paul Chiou, Wan-Jiun & Lee, Wen-Yi & Lin, Shun-Ji, 2020. "Portfolio models with return forecasting and transaction costs," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 118-130.
    289. Chenchen Li & Chongfeng Wu & Chunyang Zhou, 2021. "Forecasting equity returns: The role of commodity futures along the supply chain," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 46-71, January.
    290. Luo, Qin & Ma, Feng & Wang, Jiqian & Wu, You, 2024. "Changing determinant driver and oil volatility forecasting: A comprehensive analysis," Energy Economics, Elsevier, vol. 129(C).
    291. Qianjie Geng & Xianfeng Hao & Yudong Wang, 2024. "Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 309-325, March.
    292. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    293. Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
    294. Han, Yufeng & Hu, Ting & Yang, Jian, 2016. "Are there exploitable trends in commodity futures prices?," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 214-234.
    295. Yulin Liu & Luyao Zhang, 2022. "Cryptocurrency Valuation: An Explainable AI Approach," Papers 2201.12893, arXiv.org, revised Jul 2023.
    296. Paskalis Glabadanidis, 2017. "Timing the Market with a Combination of Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 353-394, September.
    297. Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Market Timing with Moving Averages," Econometric Institute Research Papers EI 2018-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    298. Chen, Guojin & Hong, Zhiwu & Ren, Yu, 2016. "Durable consumption and asset returns: Cointegration analysis," Economic Modelling, Elsevier, vol. 53(C), pages 231-244.
    299. Wen, Danyan & Wang, Huihui & Wang, Yudong & Xiao, Jihong, 2024. "Crude oil futures and the short-term price predictability of petroleum products," Energy, Elsevier, vol. 307(C).
    300. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    301. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    302. Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
    303. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    304. Dong, Ming & Tremblay, Andréanne, 2022. "Global weather-based trading strategies," Journal of Banking & Finance, Elsevier, vol. 143(C).
    305. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2015. "Market Sentiment and Paradigm Shifts," Research Paper Series 356, Quantitative Finance Research Centre, University of Technology, Sydney.
    306. Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018. "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, vol. 70(C), pages 472-483.
    307. Niu, Zibo & Ma, Feng & Zhang, Hongwei, 2022. "The role of uncertainty measures in volatility forecasting of the crude oil futures market before and during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 112(C).
    308. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    309. Zakamulin, Valeriy & Giner, Javier, 2022. "Time series momentum in the US stock market: Empirical evidence and theoretical analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
    310. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    311. Urquhart, Andrew & Zhang, Hanxiong, 2019. "The performance of technical trading rules in Socially Responsible Investments," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 397-411.
    312. Jixiang, Zhang & Feng, Ma, 2024. "Video apps user engagement and stock market volatility: Evidence from China," Finance Research Letters, Elsevier, vol. 64(C).
    313. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    314. Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
    315. Perry Sadorsky, 2021. "Predicting Gold and Silver Price Direction Using Tree-Based Classifiers," JRFM, MDPI, vol. 14(5), pages 1-21, April.
    316. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    317. Li, Yan & Liang, Chao & Huynh, Toan Luu Duc, 2022. "Forecasting US stock market returns by the aggressive stock-selection opportunity," Finance Research Letters, Elsevier, vol. 50(C).
    318. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
    319. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    320. Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022. "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, vol. 108(C).
    321. Deaves, Richard & Lei, Jin & Schröder, Michael, 2015. "Forecaster overconfidence and market survey performance," ZEW Discussion Papers 15-029, ZEW - Leibniz Centre for European Economic Research.
    322. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.
    323. Xue Gong & Weiguo Zhang & Weijun Xu & Zhe Li, 2022. "Uncertainty index and stock volatility prediction: evidence from international markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-44, December.
    324. Samreen Fahim Babar & Zeeshan Yasir, 2021. "Financial Institutions and Chinese Investment: The Review of China Pakistan Economic Corridor (CPEC) Policy," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 4, May - Aug.
    325. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    326. Babacar Seck & Robert J. Elliott, 2021. "Regime Switching Entropic Risk Measures on Crude Oil Pricing," Papers 2112.13041, arXiv.org.
    327. Sadorsky, Perry, 2022. "Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    328. Meng, Fanyi & Liu, Li, 2019. "Analyzing the economic sources of oil price volatility: An out-of-sample perspective," Energy, Elsevier, vol. 177(C), pages 476-486.
    329. Yensen Ni & Min-Yuh Day & Yirung Cheng & Paoyu Huang, 2022. "Can investors profit by utilizing technical trading strategies? Evidence from the Korean and Chinese stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    330. Zhang Enguang & Ma He, 2023. "An Empirical Study on Chinese Futures Market Based on Bollinger Bands Strategy and R," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 12(4), pages 1-1.
    331. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.
    332. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    333. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    334. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
    335. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    336. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    337. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
    338. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    339. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    340. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    341. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    342. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    343. Yin, Libo & Yang, Qingyuan, 2016. "Predicting the oil prices: Do technical indicators help?," Energy Economics, Elsevier, vol. 56(C), pages 338-350.
    344. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    345. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    346. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    347. Paweł Radwański, 2024. "Impact of tax changes on the risk premium of the WIG index," Bank i Kredyt, Narodowy Bank Polski, vol. 55(3), pages 333-356.
    348. Yin, Libo, 2020. "Can the intermediary capital risk predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 37(C).
    349. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
    350. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    351. Bai, Fan & Zhang, Yaqi & Chen, Zhonglu & Li, Yan, 2023. "The volatility of daily tug-of-war intensity and stock market returns," Finance Research Letters, Elsevier, vol. 55(PA).
    352. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    353. Jiaju Miao & Pawel Polak, 2023. "Online Ensemble of Models for Optimal Predictive Performance with Applications to Sector Rotation Strategy," Papers 2304.09947, arXiv.org.
    354. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    355. Li, Xiaodan & Gong, Xue & Ge, Futing & Huang, Jingjing, 2024. "Forecasting stock volatility using pseudo-out-of-sample information," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 123-135.
    356. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    357. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    358. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
    359. Ding Du & Ou Hu, 2018. "The sentiment premium and macroeconomic announcements," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 207-237, January.
    360. Barua, Ronil & Sharma, Anil K., 2022. "Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions," Finance Research Letters, Elsevier, vol. 49(C).
    361. Ikhlaas Gurrib, 2022. "Technical Analysis, Energy Cryptos and Energy Equity Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 249-267, March.
    362. Kartikay Gupta & Niladri Chatterjee, 2019. "Top performing stocks recommendation strategy for portfolio," Papers 1901.11013, arXiv.org, revised Aug 2019.
    363. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    364. Robert Hudson & Andrew Urquhart, 2021. "Technical trading and cryptocurrencies," Annals of Operations Research, Springer, vol. 297(1), pages 191-220, February.
    365. Zeng, Qing & Lu, Xinjie & Dong, Dayong & Li, Pan, 2022. "Category-specific EPU indices, macroeconomic variables and stock market return predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    366. Tan, Siow-Hooi & Lai, Ming-Ming & Tey, Eng-Xin & Chong, Lee-Lee, 2020. "Testing the performance of technical analysis and sentiment-TAR trading rules in the Malaysian stock market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    367. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
    368. Ilias Tsiakas & Jiahan Li & Haibin Zhang, 2020. "Equity Premium Prediction and the State of the Economy," Working Paper series 20-16, Rimini Centre for Economic Analysis.
    369. Jonathan A. Batten & Harald Kinateder & Niklas Wagner, 2022. "Beating the Average: Equity Premium Variations, Uncertainty, and Liquidity," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 567-588, September.
    370. Ke Yang & Nan Hu & Fengping Tian, 2024. "Forecasting Crude Oil Volatility Using the Deep Learning‐Based Hybrid Models With Common Factors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1429-1446, August.
    371. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    372. Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
    373. Wang, Jiashun & Wang, Jiqian & Ma, Feng, 2024. "International commodity market and stock volatility predictability: Evidence from G7 countries," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 62-71.
    374. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    375. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    376. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    377. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    378. Lu, Yueliang (Jacques) & Tian, Weidong, 2023. "An on-line machine learning return prediction," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    379. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
    380. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    381. Narayan, Paresh Kumar & Ahmed, Huson Ali & Narayan, Seema, 2017. "Can investors gain from investing in certain sectors?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 160-177.
    382. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
    383. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    384. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    385. Bumho Son & Yunyoung Lee & Seongwan Park & Jaewook Lee, 2023. "Forecasting global stock market volatility: The impact of volatility spillover index in spatial‐temporal graph‐based model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1539-1559, November.
    386. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
    387. Guo, Xu & Lin, Hai & Wu, Chunchi & Zhou, Guofu, 2022. "Predictive information in corporate bond yields," Journal of Financial Markets, Elsevier, vol. 59(PB).
    388. Jurdi, Doureige J., 2022. "Predicting the Australian equity risk premium," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    389. Ding Du & Xiaobing Zhao, 2017. "Financial investor sentiment and the boom/bust in oil prices during 2003–2008," Review of Quantitative Finance and Accounting, Springer, vol. 48(2), pages 331-361, February.
    390. Camillo Lento & Nikola Gradojevic, 2022. "The Profitability of Technical Analysis during the COVID-19 Market Meltdown," JRFM, MDPI, vol. 15(5), pages 1-19, April.
    391. Nusret Cakici & Christian Fieberg & Daniel Metko & Adam Zaremba, 2024. "Do Anomalies Really Predict Market Returns? New Data and New Evidence," Review of Finance, European Finance Association, vol. 28(1), pages 1-44.
    392. Eduard Baitinger, 2021. "Forecasting asset returns with network‐based metrics: A statistical and economic analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1342-1375, November.
    393. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    394. Shi, Qi, 2023. "The RP-PCA factors and stock return predictability: An aligned approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    395. Feng, Lingbing & Rao, Haicheng & Lucey, Brian & Zhu, Yiying, 2024. "Volatility forecasting on China's oil futures: New evidence from interpretable ensemble boosting trees," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1595-1615.
    396. Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.
    397. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    398. Ryan Flugum, 2021. "The trend is an analyst's friend: Analyst recommendations and market technicals," The Financial Review, Eastern Finance Association, vol. 56(2), pages 301-330, May.
    399. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
    400. Zakamulin, Valeriy & Giner, Javier, 2023. "Optimal trend-following with transaction costs," International Review of Financial Analysis, Elsevier, vol. 90(C).
    401. Hai Lin & Pengfei Liu & Cheng Zhang, 2023. "The trend premium around the world: Evidence from the stock market," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 317-358, June.
    402. Daniel Cunha Oliveira & Yutong Lu & Xi Lin & Mihai Cucuringu & Andre Fujita, 2024. "Causality-Inspired Models for Financial Time Series Forecasting," Papers 2408.09960, arXiv.org.
    403. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    404. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
    405. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    406. Chen, Yan & Liu, Yakun & Zhang, Feipeng, 2024. "Coskewness and the short-term predictability for Bitcoin return," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    407. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
    408. Ikhlaas Gurrib, 2023. "Momentum in Low Carbon and Fossil Fuel Free Equity Investing," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 461-471, September.
    409. Daniel Borup & Jorge Wolfgang Hansen & Benjamin Dybro Liengaard & Erik Christian Montes Schütte, 2023. "Quantifying investor narratives and their role during COVID‐19," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 512-532, June.
    410. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    411. Hui Zeng & Ben R Marshall & Nhut H Nguyen & Nuttawat Visaltanachoti, 2022. "Are individual stock returns predictable?," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 135-162, February.
    412. Pan, Zheyao & Chan, Kam Fong, 2018. "A new government bond volatility index predictor for the U.S. equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 200-215.
    413. Tzu-Pu Chang & Yu-Cheng Chang & Po-Ching Chou, 2022. "The Trend is Your Friend: A Note on An Ensemble Learning Approach to Finding It," Bulletin of Applied Economics, Risk Market Journals, vol. 9(1), pages 19-25.
    414. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    415. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    416. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    417. Qingjing Zhang & Taufiq Choudhry & Jing-Ming Kuo & Xiaoquan Liu, 2021. "Does liquidity drive stock market returns? The role of investor risk aversion," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 929-958, October.
    418. Li Liu & Xianfeng Hao & Yudong Wang, 2024. "Solving the Forecast Combination Puzzle Using Double Shrinkages," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 714-741, June.
    419. Liu, Li & Pan, Zhiyuan, 2020. "Forecasting stock market volatility: The role of technical variables," Economic Modelling, Elsevier, vol. 84(C), pages 55-65.
    420. Dominik Wolff & Ulrich Neugebauer, 2019. "Tree-based machine learning approaches for equity market predictions," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 273-288, July.
    421. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    422. Luo, Suyuan & Lin, Xudong & Zheng, Zunxin, 2019. "A novel CNN-DDPG based AI-trader: Performance and roles in business operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 68-79.
    423. Navratil, Robert & Taylor, Stephen & Vecer, Jan, 2021. "On equity market inefficiency during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 77(C).
    424. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    425. Chu, Xiaojun & Wan, Xinmin & Qiu, Jianying, 2023. "The relative importance of overnight sentiment versus trading-hour sentiment in volatility forecasting," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    426. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    427. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    428. Ibrahim Filiz & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2021. "Sticky Stock Market Analysts," JRFM, MDPI, vol. 14(12), pages 1-27, December.
    429. Zeng, Qing & Lu, Xinjie & Li, Tao & Wu, Lan, 2022. "Jumps and stock market variance during the COVID-19 pandemic: Evidence from international stock markets," Finance Research Letters, Elsevier, vol. 48(C).
    430. Maria Ludovica Drudi & Federico Calogero Nucera, 2022. "Economic fundamentals and stock market valuation: a CAPE-based approach," Temi di discussione (Economic working papers) 1393, Bank of Italy, Economic Research and International Relations Area.
    431. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    432. Xu, Yahua & Bouri, Elie & Saeed, Tareq & Wen, Zhuzhu, 2020. "Intraday return predictability: Evidence from commodity ETFs and their related volatility indices," Resources Policy, Elsevier, vol. 69(C).
    433. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    434. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    435. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    436. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
    437. Ikhlaas Gurrib & Olga Starkova & Dalia Hamdan, 2024. "Trading Momentum in the U.S. Crude Oil Futures Market," International Journal of Energy Economics and Policy, Econjournals, vol. 14(5), pages 593-604, September.
    438. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    439. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    440. Feng He & Libo Yin, 2021. "Shocks to the equity capital ratio of financial intermediaries and the predictability of stock return volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 945-962, September.
    441. Wang, Lu & Ma, Feng & Hao, Jianyang & Gao, Xinxin, 2021. "Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?," International Review of Financial Analysis, Elsevier, vol. 76(C).
    442. Goh, Jeremy C. & Jiang, Fuwei & Tu, Jun & Wang, Yuchen, 2013. "Can US economic variables predict the Chinese stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 22(C), pages 69-87.
    443. Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).
    444. Shah, Imran Hussain & Schmidt-Fischer, Francesca & Malki, Issam & Hatfield, Richard, 2019. "A structural break approach to analysing the impact of the QE portfolio balance channel on the US stock market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 204-220.
    445. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    446. Perry Sadorsky, 2021. "A Random Forests Approach to Predicting Clean Energy Stock Prices," JRFM, MDPI, vol. 14(2), pages 1-20, January.
    447. Yong Shi & Bo Li & Wen Long & Wei Dai, 2022. "Method for Improving the Performance of Technical Analysis Indicators By Neural Network Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1027-1068, March.
    448. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
    449. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.
    450. Zheng, Yan & Wen, Fenghua & Deng, Hanshi & Zeng, Aiqing, 2022. "The relationship between carbon market attention and the EU CET market: Evidence from different market conditions," Finance Research Letters, Elsevier, vol. 50(C).
    451. Dichtl, Hubert & Drobetz, Wolfgang & Otto, Tizian, 2023. "Forecasting Stock Market Crashes via Machine Learning," Journal of Financial Stability, Elsevier, vol. 65(C).
    452. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    453. Yin, Libo & Feng, Jiabao & Han, Liyan, 2021. "Systemic risk in international stock markets: Role of the oil market," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 592-619.
    454. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    455. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
    456. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    457. Guohao Tang & Fuwei Jiang & Xinlin Qi & Nan Huang, 2021. "It takes two to tango: Fundamental timing in stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5259-5277, October.
    458. Lu, Xinjie & Lang, Qiaoqi, 2023. "Categorial economic policy uncertainty indices or Twitter-based uncertainty indices? Evidence from Chinese stock market," Finance Research Letters, Elsevier, vol. 55(PB).
    459. Nicholas Apergis & Rangan Gupta, 2016. "Can Weather Conditions in New York Predict South African Stock Returns?," Working Papers 201634, University of Pretoria, Department of Economics.
    460. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    461. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.

  2. Jay Shanken & Guofu Zhou, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," CEMA Working Papers 275, China Economics and Management Academy, Central University of Finance and Economics.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. M. Reza Bradrania & Maurice Peat & Stephen Satchell, 2022. "Liquidity Costs, Idiosyncratic Volatility and Expected Stock Returns," Papers 2211.04695, arXiv.org.
    3. Mr. Shaun K. Roache, 2008. "Commodities and the Market Price of Risk," IMF Working Papers 2008/221, International Monetary Fund.
    4. Elsas, Ralf & Florysiak, David, 2008. "Empirical Capital Structure Research: New Ideas, Recent Evidence, and Methodological Issues," Discussion Papers in Business Administration 4743, University of Munich, Munich School of Management.
    5. Hammami, Yacine & Lindahl, Anna, 2014. "An intertemporal capital asset pricing model with bank credit growth as a state variable," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 14-28.
    6. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
    7. Kleibergen, Frank, 2009. "Tests of risk premia in linear factor models," Journal of Econometrics, Elsevier, vol. 149(2), pages 149-173, April.
    8. Du, Ding & Hu, Ou, 2012. "Foreign exchange volatility and stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1202-1216.
    9. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    10. Bernoth, Kerstin & von Hagen, Jürgen & de Vries, Caspar, 2022. "The Term Structure of Currency Futures' Risk Premia," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 54(1), pages 5-38.
    11. Murtazashvili, Irina & Vozlyublennaia, Nadia, 2012. "The performance of cross-sectional regression tests of the CAPM with non-zero pricing errors," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1057-1066.
    12. Raymond Kan & Cesare Robotti, 2006. "Specification tests of asset pricing models using excess returns," FRB Atlanta Working Paper 2006-10, Federal Reserve Bank of Atlanta.
    13. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    14. Massimo Guidolin & Erwin Hansen & Martín Lozano-Banda, 2018. "Portfolio Performance of Linear SDF Models: An Out-of-Sample Assessment," BAFFI CAREFIN Working Papers 1885, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    15. Yuriy Kitsul & Marcelo Ochoa, 2016. "Funding Liquidity Risk and the Cross-section of MBS Returns," Finance and Economics Discussion Series 2016-052, Board of Governors of the Federal Reserve System (U.S.).
    16. Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
    17. Pierluigi Balduzzi & Cesare Robotti, 2005. "Asset-pricing models and economic risk premia: a decomposition," FRB Atlanta Working Paper 2005-13, Federal Reserve Bank of Atlanta.
    18. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "Estimation of large dimensional conditional factor models in finance," Working Papers unige:125031, University of Geneva, Geneva School of Economics and Management.
    19. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    20. Asparouhova, Elena & Bessembinder, Hendrik & Kalcheva, Ivalina, 2010. "Liquidity biases in asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 215-237, May.
    21. Lozano, Martín & Rubio, Gonzalo, 2011. "Evaluating alternative methods for testing asset pricing models with historical data," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 136-146, January.
    22. Ossola, Elisa & Gagilardini, Patrick & Scaillet, Olivier, 2015. "Time-varying risk premium in large cross-sectional equity datasets," Working Papers unige:76321, University of Geneva, Geneva School of Economics and Management.
    23. Hanno Lustig & Adrien Verdelhan, 2011. "The Cross-Section of Foreign Currency Risk Premia and Consumption Growth Risk: Reply," American Economic Review, American Economic Association, vol. 101(7), pages 3477-3500, December.
    24. Beaulieu, Marie-Claude & Gagnon, Marie-Hélène & Khalaf, Lynda, 2016. "Less is more: Testing financial integration using identification-robust asset pricing models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 171-190.
    25. Solène Collot & Tobias Hemauer, 2021. "A literature review of new methods in empirical asset pricing: omitted-variable and errors-in-variable bias," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(1), pages 77-100, March.
    26. Ferreira, Eva & Gil-Bazo, Javier & Orbe, Susan, 2008. "Nonparametric estimation of conditional beta pricing models," DEE - Working Papers. Business Economics. WB wb082403, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    27. Bauder, David & Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2020. "Bayesian inference of the multi-period optimal portfolio for an exponential utility," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    28. Enrico G. De Giorgi & Thierry Post & Atakan Yalcin, 2012. "A Concave Security Market Line," Koç University-TUSIAD Economic Research Forum Working Papers 1211, Koc University-TUSIAD Economic Research Forum.
    29. Zaremba, Adam & Czapkiewicz, Anna, 2017. "Digesting anomalies in emerging European markets: A comparison of factor pricing models," Emerging Markets Review, Elsevier, vol. 31(C), pages 1-15.
    30. Ravi Jagannathan & Srikant Marakani & Hitoshi Takehara & Yong Wang, 2012. "Calendar Cycles, Infrequent Decisions, and the Cross Section of Stock Returns," Management Science, INFORMS, vol. 58(3), pages 507-522, March.
    31. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    32. Craig Burnside, 2016. "Identification and Inference in Linear Stochastic Discount Factor Models with Excess Returns," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 295-330.
    33. Richard T. Baillie & Fabio Calonaci & George Kapetanios, 2019. "Hierarchical Time Varying Estimation of a Multi Factor Asset Pricing Model," Working Papers 879, Queen Mary University of London, School of Economics and Finance.
    34. Czapkiewicz, Anna & Wójtowicz, Tomasz & Zaremba, Adam, 2023. "Idiosyncratic risk and cross-section of stock returns in emerging European markets," Economic Modelling, Elsevier, vol. 124(C).
    35. Du, Ding & Hu, Ou, 2015. "The world market risk premium and U.S. macroeconomic announcements," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 75-97.
    36. Ekaterini Panopoulou & Koubouros, M. & Malliaropulos, D., 2005. "Long-Run Cash-Flow and Discount-Rate Risks in the Cross-Section of US Returns," Economics Department Working Paper Series n1580505, Department of Economics, National University of Ireland - Maynooth.
    37. Ferreira, Eva & Gil-Bazo, Javier & Orbe, Susan, 2011. "Conditional beta pricing models: A nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3362-3382.
    38. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2012. "The Adverse Impact of Gradual Temperature Change on Capital Investment," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124676, Agricultural and Applied Economics Association.
    39. Tarek Eldomiaty & Islam Azzam & Karim Tarek Hamed Afifi & Mohamed Hashim Rashwan, 2024. "An Alignment of Financial Signaling and Stock Return Synchronicity," JRFM, MDPI, vol. 17(4), pages 1-12, April.
    40. Gao, Feng & He, Ziwen, 2024. "Digital economy, land resource misallocation and urban carbon emissions in Chinese resource-based cities," Resources Policy, Elsevier, vol. 91(C).
    41. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
    42. Mohammad Q. M. AL-Momani, 2016. "A Modified Fama and French (1993) Three-factor Asset Pricing Model: Evidence from the UK Equity Market," Applied Economics and Finance, Redfame publishing, vol. 3(3), pages 50-64, August.
    43. Joanna Olbry�, 2014. "Is illiquidity risk priced? The case of the Polish medium-size emerging stock market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(6), pages 513�536-5.
    44. Yacine Hammami, 2014. "An empirical investigation of asset pricing models under divergent lending and borrowing rates," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(3), pages 263-279, August.
    45. Raymond Kan & Cesare Robotti & Jay Shanken, 2009. "Pricing model performance and the two-pass cross-sectional regression methodology," FRB Atlanta Working Paper 2009-11, Federal Reserve Bank of Atlanta.
    46. Du, Ding, 2013. "Another look at the cross-section and time-series of stock returns: 1951 to 2011," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 130-146.
    47. Craig Burnside & Mario Cerrato & Zhekai Zhang, 2023. "Foreign exchange order flow as a risk factor," Working Papers 2023_03, Business School - Economics, University of Glasgow.
    48. Sudipta Das, 2019. "Asset Pricing Test Using Alternative Sets of Portfolios: Evidence from India," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(3), pages 339-354, September.
    49. Couch, Robert & Wu, Wei, 2012. "Private investment and public equity returns," Journal of Economics and Business, Elsevier, vol. 64(2), pages 160-184.
    50. Silvo Dajčman & Mejra Festić & Alenka Kavkler, 2013. "Multiscale test of CAPM for three Central and Eastern European stock markets," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(1), pages 54-76, February.
    51. Kodongo, Odongo & Ojah, Kalu, 2014. "The conditional pricing of currency and inflation risks in Africa's equity markets," MPRA Paper 56100, University Library of Munich, Germany.
    52. Cujean, Julien & Andrei, Daniel & Wilson, Mungo, 2018. "The Lost Capital Asset Pricing Model," CEPR Discussion Papers 12607, C.E.P.R. Discussion Papers.
    53. Zaremba, Adam & Czapkiewicz, Anna, 2017. "The cross section of international government bond returns," Economic Modelling, Elsevier, vol. 66(C), pages 171-183.
    54. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
    55. Mohrschladt, Hannes & Nolte, Sven, 2018. "A new risk factor based on equity duration," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 126-135.
    56. Simlai, Prodosh, 2014. "Persistence of ex-ante volatility and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 253-261.
    57. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2017. "Temperature shocks and the cost of equity capital: Implications for climate change perceptions," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 18-34.
    58. M. Hashem Pesaran & Ron P. Smith, 2021. "Arbitrage Pricing Theory, the Stochastic Discount Factor and Estimation of Risk Premia from Portfolios," CESifo Working Paper Series 9001, CESifo.
    59. Borup, Daniel, 2019. "Asset pricing model uncertainty," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 166-189.
    60. Maio, Paulo & Santa-Clara, Pedro, 2012. "Multifactor models and their consistency with the ICAPM," Journal of Financial Economics, Elsevier, vol. 106(3), pages 586-613.
    61. De Giorgi, Enrico G. & Post, Thierry & Yalçın, Atakan, 2019. "A concave security market line," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 65-81.
    62. Iqbal, Javed & Brooks, Robert & Galagedera, Don U.A., 2010. "Testing conditional asset pricing models: An emerging market perspective," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 897-918, September.
    63. Seungho Baek & Jeong Wan Lee & Kyong Joo Oh & Myoungji Lee, 2020. "Yield curve risks in currency carry forwards," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 651-670, April.
    64. M. Hashem Pesaran & Ron P. Smith, 2019. "The Role of Factor Strength and Pricing Errors for Estimation and Inference in Asset Pricing Models," CESifo Working Paper Series 7919, CESifo.
    65. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    66. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    67. Marie-Claude Beaulieu & Jean-Marie Dufour & Lynda Khalaf, 2020. "Arbitrage Pricing, Weak Beta, Strong Beta: Identification-Robust and Simultaneous Inference," CIRANO Working Papers 2020s-30, CIRANO.
    68. Matias Cattaneo & Richard K. Crump & Weining Wang, 2024. "Beta-sorted portfolios," CeMMAP working papers 20/24, Institute for Fiscal Studies.
    69. Ahn, Seung C. & Perez, M. Fabricio & Gadarowski, Christopher, 2013. "Two-pass estimation of risk premiums with multicollinear and near-invariant betas," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 1-17.
    70. Duran-Vazquez, Rocio & Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2011. "Valuación de acciones mexicanas mediante los modelos de Ohlson y Ohlson-Beta para firmas con ciclos de corto y largo plazos: Un análisis de cointegración [Valuation of Mexican stocks with the Olhso," MPRA Paper 33054, University Library of Munich, Germany.
    71. Ailie Charteris & Mukashema Rwishema & Tafadzwa-Hidah Chidede, 2018. "Asset Pricing and Momentum: A South African Perspective," Journal of African Business, Taylor & Francis Journals, vol. 19(1), pages 62-85, January.
    72. Enrique Sentana, 2008. "The Econometrics of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
    73. Ravi Jagannathan & Srikant Marakani, 2015. "Price-Dividend Ratio Factor Proxies for Long-Run Risks," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 5(1), pages 1-47.
    74. Massimo Guidolin & Martin Lozano & Juan Arismendi Zambrano, "undated". "Multifactor Empirical Asset Pricing Under Higher-Order Moment Variations," Economics Department Working Paper Series n304-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    75. Piet Sercu & Martina Vandebroek & Tom Vinaimont, 2008. "Thin‐Trading Effects in Beta: Bias v. Estimation Error," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(9‐10), pages 1196-1219, November.
    76. Gregory, Richard P., 2021. "The pricing of global temperature shocks in the cost of equity capital," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    77. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda & Melin, Olena, 2023. "Identification-robust beta pricing, spanning, mimicking portfolios, and the benchmark neutrality of catastrophe bonds," Journal of Econometrics, Elsevier, vol. 236(1).
    78. Ding Du & Ou Hu, 2018. "The sentiment premium and macroeconomic announcements," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 207-237, January.
    79. Ilan Cooper & Paulo Maio, 2019. "Asset Growth, Profitability, and Investment Opportunities," Management Science, INFORMS, vol. 65(9), pages 3988-4010, September.
    80. Grauer, Robert R. & Janmaat, Johannus A., 2009. "On the power of cross-sectional and multivariate tests of the CAPM," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 775-787, May.
    81. Antoine Giannetti, 2024. "A simple test of misspecification for linear asset pricing models," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(3), pages 305-330, September.
    82. M. Hashem Pesaran & Run Smith, 2021. "Arbitrage pricing theory, the stochastic discount factor and estimation of risk premia in portfolios," BCAM Working Papers 2108, Birkbeck Centre for Applied Macroeconomics.
    83. Timothy Erickson & Toni M. Whited, 2012. "Treating Measurement Error in Tobin's q," The Review of Financial Studies, Society for Financial Studies, vol. 25(4), pages 1286-1329.
    84. Shujing Li & Jiaping Qiu, 2014. "Financial Product Differentiation over the State Space in the Mutual Fund Industry," Management Science, INFORMS, vol. 60(2), pages 508-520, February.
    85. Tarek Ibrahim Eldomiaty & Sahar Charara & Wael Mostafa, 2011. "Monitoring the Systematic and Unsystematic Risk in Dubai General Index," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 10(3), pages 285-310, December.
    86. Ai He & Guofu Zhou, 2023. "Diagnostics for asset pricing models," Financial Management, Financial Management Association International, vol. 52(4), pages 617-642, December.
    87. Balakumar, Suganya & Dash, Saumya Ranjan & Maitra, Debasish & Kang, Sang Hoon, 2022. "Do oil price shocks have any implications for stock return momentum?," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 637-663.
    88. M. Hashem Pesaran & Ron P. Smith, 2021. "Factor Strengths, Pricing Errors, and Estimation of Risk Premia," CESifo Working Paper Series 8947, CESifo.
    89. Durand, Robert B. & Lan, Yihui & Ng, Andrew, 2011. "Conditional beta: Evidence from Asian emerging markets," Global Finance Journal, Elsevier, vol. 22(2), pages 130-153.
    90. Pin-Huang Chou & Guofu Zhou, 2006. "Using Bootstrap to Test Portfolio Efficiency," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 217-249, November.
    91. Bai, Jushan & Zhou, Guofu, 2015. "Fama–MacBeth two-pass regressions: Improving risk premia estimates," Finance Research Letters, Elsevier, vol. 15(C), pages 31-40.
    92. Kodongo, Odongo & Ojah, Kalu, 2014. "Conditional pricing of currency risk in Africa's equity markets," Emerging Markets Review, Elsevier, vol. 21(C), pages 133-155.
    93. Ma, Xiuli & Zhang, Xindong & Liu, Weimin, 2021. "Further tests of asset pricing models: Liquidity risk matters," Economic Modelling, Elsevier, vol. 95(C), pages 255-273.
    94. Amihud, Yakov & Noh, Joonki, 2021. "The pricing of the illiquidity factor’s conditional risk with time-varying premium," Journal of Financial Markets, Elsevier, vol. 56(C).
    95. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    96. Kerstin Bernoth & Jürgen von Hagen & Casper G. de Vries, 2020. "Currency Futures' Risk Premia and Risk Factors," Discussion Papers of DIW Berlin 1866, DIW Berlin, German Institute for Economic Research.
    97. Park, Dojoon & Kang, Yong Joo & Eom, Young Ho, 2024. "Asset pricing tests for pandemic risk," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1314-1334.
    98. Guermat, Cherif & Freeman, Mark C., 2010. "A net beta test of asset pricing models," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 1-9, January.
    99. Xiangying Meng & Xianhua Wei & Yinchao Chen, 2019. "Estimation on Risk Factor Loading based on Mixed Vine Copula," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 9(3), pages 1-6.
    100. Ding Du & Ou Hu & Xiaobing Zhao, 2016. "Currency Risk Premium And U.S. Macroeconomic Announcement," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 39(4), pages 359-388, December.

  3. Campbell R. Harvey & Bruno Solnik & Guofu Zhou, 2002. "What Determines Expected International Asset Returns?," CEMA Working Papers 503, China Economics and Management Academy, Central University of Finance and Economics.

    Cited by:

    1. Harvey, Campbell R, 1995. "Predictable Risk and Returns in Emerging Markets," The Review of Financial Studies, Society for Financial Studies, vol. 8(3), pages 773-816.
    2. Phylaktis, Kate & Xia, Lichuan, 2006. "Sources of firms' industry and country effects in emerging markets," Journal of International Money and Finance, Elsevier, vol. 25(3), pages 459-475, April.
    3. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    4. Christophe Chamley, 2006. "Complementarities in information acquisition with short-term trades," Boston University - Department of Economics - Working Papers Series WP2006-042, Boston University - Department of Economics.
    5. Haque Mahfuzul & Hassan M. Kabir & Maroney Neal C & Sackley William H, 2004. "An Empirical Examination of Stability, Predictability, and Volatility of Middle Eastern and African Emerging Stock Markets," Review of Middle East Economics and Finance, De Gruyter, vol. 2(1), pages 18-41, April.
    6. Nitschka, Thomas, 2018. "Bond market evidence of time variation in exposures to global risk factors and the role of US monetary policy," Journal of International Money and Finance, Elsevier, vol. 83(C), pages 44-54.
    7. Hanno Lustig, 2004. "The Cross-Section of Foreign Currency Risk Premia and US Consumption Growth Risk (joint with Adrien Verdelhan)(updated February 2006)," UCLA Economics Online Papers 303, UCLA Department of Economics.
    8. Schneider, Martin & Albuquerque, Rui & Bauer, Gregory, 2005. "International Equity Flows and Returns: A Quantitative Equilibrium Approach," CEPR Discussion Papers 5159, C.E.P.R. Discussion Papers.
    9. Barr, David G. & Priestley, Richard, 2004. "Expected returns, risk and the integration of international bond markets," Journal of International Money and Finance, Elsevier, vol. 23(1), pages 71-97, February.
    10. Lee, Wai, 1997. "Covariance risk, consumption risk, and international stock market returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 37(2), pages 491-510.
    11. Marina Emiris, 2002. "Measuring capital market integration," BIS Papers chapters, in: Bank for International Settlements (ed.), Market functioning and central bank policy, volume 12, pages 200-221, Bank for International Settlements.
    12. Andrea Beltratti & Claudio Morana, 2006. "Net Inflows and Time-Varying Alphas: The Case of Hedge Funds," ICER Working Papers 30-2006, ICER - International Centre for Economic Research.
    13. Andrew Ang & Joseph Chen, 2005. "CAPM Over the Long Run: 1926-2001," NBER Working Papers 11903, National Bureau of Economic Research, Inc.
    14. Wayne Ferson & Campbell R. Harvey, 1994. "An Exploratory Investigation of the Fundamental Determinants of National Equity Market Returns," NBER Chapters, in: The Internationalization of Equity Markets, pages 59-147, National Bureau of Economic Research, Inc.
    15. Mateus, Tiago, 2004. "The risk and predictability of equity returns of the EU accession countries," Emerging Markets Review, Elsevier, vol. 5(2), pages 241-266, June.
    16. Du, Ding & Hu, Ou, 2015. "The world market risk premium and U.S. macroeconomic announcements," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 75-97.
    17. Hanno Lustig & Nikolai Roussanov & Adrien Verdelhan, 2008. "Common Risk Factors in Currency Markets," NBER Working Papers 14082, National Bureau of Economic Research, Inc.
    18. Eric Girard & Amit Sinha, 2008. "Risk and Return in the Next Frontier," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 7(1), pages 43-80, January.
    19. Hanno Lustig & Adrien Verdelhan, 2006. "The Cross-Section of Foreign Currency Risk Premia and Consumption Growth Risk," Boston University - Department of Economics - Working Papers Series WP2006-045, Boston University - Department of Economics.
    20. Jushan Bai & Shuzhong Shi, 2011. "Estimating High Dimensional Covariance Matrices and its Applications," Annals of Economics and Finance, Society for AEF, vol. 12(2), pages 199-215, November.
    21. Samson, Lucie, 2013. "Asset prices and exchange risk: Empirical evidence from Canada," Research in International Business and Finance, Elsevier, vol. 28(C), pages 35-44.
    22. Girard, Eric & Omran, Mohamed, 2007. "What are the risks when investing in thin emerging equity markets: Evidence from the Arab world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(1), pages 102-123, February.
    23. Hanno Lustig & Adrien Verdelhan, 2009. "Comment on "Carry Trades and Currency Crashes"," NBER Chapters, in: NBER Macroeconomics Annual 2008, Volume 23, pages 361-384, National Bureau of Economic Research, Inc.
    24. Qin, Weiping & Cho, Sungjun & Hyde, Stuart, 2022. "Measuring market integration during crisis periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    25. Geert Bekaert & Campbell R. Harvey, 1994. "Time-Varying World Market Integration," NBER Working Papers 4843, National Bureau of Economic Research, Inc.
    26. Groth, Charlotta & Zampolli, Fabrizio, 2010. "Macroeconomic stability and the real interest rate: a cross-country analysis," Discussion Papers 30, Monetary Policy Committee Unit, Bank of England.
    27. Keiber, Karl Ludwig & Samyschew, Helene, 2016. "The pricing of sentiment risk in European stock markets," Discussion Papers 384, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    28. Turtle, H.J. & Zhang, Chengping, 2012. "Time-varying performance of international mutual funds," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 334-348.
    29. Harry J. Turtle & Chengping Zhang, 2015. "Structural breaks and portfolio performance in global equity markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 909-922, June.
    30. Rui Albuquerque & Gregory Bauer & Martin Schneider, 2004. "Characterizing Asymmetric Information in International Equity Markets," International Finance 0405005, University Library of Munich, Germany.
    31. Tom A. FEARNLEY, 2002. "Tests of an International Capital Asset Pricing Model with Stocks and Government Bonds and Regime Switching Prices of Risk and Intercepts," FAME Research Paper Series rp97, International Center for Financial Asset Management and Engineering.
    32. Keiber, Karl Ludwig & Samyschew, Helene, 2017. "The world price of sentiment risk," Global Finance Journal, Elsevier, vol. 32(C), pages 62-82.
    33. Doriana Ruffino & Jonathan Treussard, 2006. "A Study of Inaction in Investment Games via the Early Exercise Premium Representation," Boston University - Department of Economics - Working Papers Series WP2006-040, Boston University - Department of Economics.
    34. Selcuk Caner & Zeynep Onder, 2005. "Sources of volatility in stock returns in emerging markets," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 929-941.
    35. Gregory Bauer & Antonio Diez de los Rios, 2012. "An International Dynamic Term Structure Model with Economic Restrictions and Unspanned Risks," Staff Working Papers 12-5, Bank of Canada.
    36. Hanno Lustig & Adrien Verdelhan, 2005. "The Cross-Section of Currency Risk Premia and US Consumption Growth Risk," NBER Working Papers 11104, National Bureau of Economic Research, Inc.
    37. Grossmann, Axel & Simpson, Marc W., 2015. "Bid-ask spreads, deviations from PPP and the forward prediction error: The case of the British pound and the euro," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 124-139.
    38. Alexandra HOROBET & Livia ILIE, 2009. "On The Exchange Rate Risk Contribution To The Performance Of International Investments: The Case Of Romania," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 3, pages 57-83, May.
    39. Demir Bektić & Britta Hachenberg & Dirk Schiereck, 2020. "Factor-based investing in government bond markets: a survey of the current state of research," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 94-105, March.
    40. Hanno Lustig & Robert J. Richmond, 2017. "Gravity in FX R-Squared: Understanding the Factor Structure in Exchange Rates," NBER Working Papers 23773, National Bureau of Economic Research, Inc.
    41. De Moor, Lieven & Sercu, Piet, 2011. "Country versus sector factors in equity returns: The roles of non-unit exposures," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 64-77, January.
    42. Li, Yulin, 2021. "Investor sentiment and sovereign bonds," Journal of International Money and Finance, Elsevier, vol. 115(C).
    43. Posedel Šimović, Petra & Tkalec, Marina & Vizek, Maruška & Lee, Junsoo, 2016. "Time-varying integration of the sovereign bond markets in European post-transition economies," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 30-40.
    44. Bange, Mary M. & Khang, Kenneth & Miller Jr., Thomas W., 2008. "Benchmarking the performance of recommended allocations to equities, bonds, and cash by international investment houses," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 363-386, June.
    45. Tom A. FEARNLEY, 2002. "Estimation of an International Capital Asset Pricing Model with Stocks and Government Bonds," FAME Research Paper Series rp95, International Center for Financial Asset Management and Engineering.
    46. Li, Yulin & Wald, John K. & Wang, Zijun, 2020. "Sovereign bonds, coskewness, and monetary policy regimes," Journal of Financial Stability, Elsevier, vol. 50(C).

  4. Raymond Kan & Guofu Zhou, 2001. "Tests of Mean-Variance Spanning," CEMA Working Papers 539, China Economics and Management Academy, Central University of Finance and Economics.

    Cited by:

    1. Glabadanidis, Paskalis, 2009. "Measuring the economic significance of mean-variance spanning," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(2), pages 596-616, May.
    2. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-Fit in Multivariate Regressions with Application to Asset Pricing Models," Cahiers de recherche 07-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    3. Dufour, Jean-Marie & Beaulieu, Marie-Claude & Khalaf, Lynda, 2003. "Testing mean-variance efficiency in CAPM with possibly non-gaussian errors: an exact simulation-based approach," Discussion Paper Series 1: Economic Studies 2003,01, Deutsche Bundesbank.
    4. Romain Deguest & Lionel Martellini & Vincent Milhau, 2018. "A Reinterpretation of the Optimal Demand for Risky Assets in Fund Separation Theorems," Management Science, INFORMS, vol. 64(9), pages 4333-4347, September.
    5. Sina Ehsani & Juhani T. Linnainmaa, 2019. "Factor Momentum and the Momentum Factor," NBER Working Papers 25551, National Bureau of Economic Research, Inc.
    6. Bernd Scherer, 2021. "Adding alternative assets: return enhancement, diversification or hedging?," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 437-442, October.
    7. Pirgaip, Burak & Arslan-Ayaydin, Özgür & Karan, Mehmet Baha, 2021. "Do Sukuk provide diversification benefits to conventional bond investors? Evidence from Turkey," Global Finance Journal, Elsevier, vol. 50(C).
    8. Janda, K & Rausser, G & Svárovská, B, 2014. "Can investment in microfinance funds improve risk-return characteristics of a portfolio?," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt61k33595, Department of Agricultural & Resource Economics, UC Berkeley.
    9. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models," Cahiers de recherche 2003-08, Universite de Montreal, Departement de sciences economiques.
    10. Karl Demers‐Bélanger & Van Son Lai, 2020. "Diversification benefits of cat bonds: An in‐depth examination," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 29(5), pages 165-228, December.
    11. Kempf, Alexander & Memmel, Christoph, 2005. "On the estimation of the global minimum variance portfolio," CFR Working Papers 05-02, University of Cologne, Centre for Financial Research (CFR).
    12. Tim Schmitz & Ingo Hoffmann, 2020. "Re-evaluating cryptocurrencies' contribution to portfolio diversification -- A portfolio analysis with special focus on German investors," Papers 2006.06237, arXiv.org, revised Aug 2020.
    13. Lin, Qi, 2022. "Understanding idiosyncratic momentum in the Chinese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    14. Jonathan Fletcher, 2018. "An Examination of the Benefits of Factor Investing in U.K. Stock Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(4), pages 154-170, April.
    15. Shumi Akhtar & Farida Akhtar & Maria Jahromi & Kose John, 2023. "Volatility linkages and value gains from diversifying with Islamic assets," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(8), pages 1495-1528, October.
    16. Fletcher, Jonathan & Marshall, Andrew, 2005. "An empirical examination of the benefits of international diversification," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(5), pages 455-468, December.
    17. Tim A. Kroencke & Felix Schindler & Andreas Schrimpf, 2011. "International Diversification Benefits with Foreign Exchange Investment Styles," CREATES Research Papers 2011-10, Department of Economics and Business Economics, Aarhus University.
    18. Yan, Lei & Garcia, Philip, 2017. "Portfolio investment: Are commodities useful?," Journal of Commodity Markets, Elsevier, vol. 8(C), pages 43-55.
    19. Stelios Arvanitis & O. Scaillet & Nikolas Topaloglou, 2020. "Spanning analysis of stock market anomalies under Prospect Stochastic Dominance," Swiss Finance Institute Research Paper Series 20-18, Swiss Finance Institute.
    20. Giovanni Petrella, 2005. "Are Euro Area Small Cap Stocks an Asset Class? Evidence from Mean‐Variance Spanning Tests," European Financial Management, European Financial Management Association, vol. 11(2), pages 229-253, March.
    21. Gur Huberman & Zhenyu Wang, 2005. "Arbitrage pricing theory," Staff Reports 216, Federal Reserve Bank of New York.
    22. Fays, Boris & Papageorgiou, Nicolas & Lambert, Marie, 2021. "Risk optimizations on basis portfolios: The role of sorting," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 136-163.
    23. Conlon, Thomas & Cotter, John & Ropotos, Ioannis, 2024. "Diversification with globally integrated US stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    24. Charles Cao & Jing-Zhi Huang, 2007. "Determinants of S&P 500 index option returns," Review of Derivatives Research, Springer, vol. 10(1), pages 1-38, January.
    25. Galvani, Valentina & Plourde, Andre, 2009. "Portfolio Diversification in Energy Markets," Working Papers 2009-6, University of Alberta, Department of Economics.
    26. Erwan Le Saout, 2017. "Performance of the Microfinance Investment Vehicles," Applied Economics and Finance, Redfame publishing, vol. 4(6), pages 42-52, November.
    27. Sofiane Aboura & Julien Chevallier, 2014. "The cross-market index for volatility surprise," Journal of Asset Management, Palgrave Macmillan, vol. 15(1), pages 7-23, February.
    28. Galvani, Valentina, 2007. "Underlying assets for which options complete the market," Finance Research Letters, Elsevier, vol. 4(1), pages 59-66, March.
    29. Francisco Peñaranda & Enrique Sentana, 2008. "Spanning tests in return and stochastic discount factor mean-variance frontiers: A unifying approach," Economics Working Papers 1101, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2010.
    30. Carmine Trecroci, 2010. "Multifactors risk loadings and abnormal returns under uncertainty and learning," Working Papers 1011, University of Brescia, Department of Economics.
    31. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
    32. Galvani, Valentina & Faychuk, Vita, 2022. "The Mean-Variance Core of Cryptocurrencies: When More is Not Better," Working Papers 2022-4, University of Alberta, Department of Economics.
    33. Paskalis Glabadanidis & Ivan Obaydin & Ralf Zurbruegg, 2012. "RAFI® replication: Easier done than said?," Journal of Asset Management, Palgrave Macmillan, vol. 13(3), pages 210-225, June.
    34. Andreas Charitou & Andreas Makris & George P. Nishiotis, 2006. "Closed-End Country Funds and International Diversification," Multinational Finance Journal, Multinational Finance Journal, vol. 10(3-4), pages 251-276, September.
    35. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla I. & Masih, A. Mansur M., 2014. "The Role of Islamic Asset Classes in the Diversified Portfolios: Mean Variance Spanning Test," MPRA Paper 56857, University Library of Munich, Germany.
    36. Fletcher, Jonathan, 2018. "An empirical examination of the diversification benefits of U.K. international equity closed-end funds," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 23-34.
    37. Abhyankar, Abhay & Ho, Keng-Yu, 2007. "Long-horizon event studies and event firm portfolio weights: Evidence from U.K. rights issues re-visited," International Review of Financial Analysis, Elsevier, vol. 16(1), pages 61-80.
    38. Fogarty, James Joseph & Sadler, Rohan, 2012. "To Save or Savour: A Review of Wine Investment," Working Papers 139663, University of Western Australia, School of Agricultural and Resource Economics.
    39. Paul Karehnke & Frans de Roon, 2020. "Spanning Tests for Assets with Option-Like Payoffs: The Case of Hedge Funds," Management Science, INFORMS, vol. 66(12), pages 5969-5989, December.
    40. Marie Briere & Kim Oosterlinck & Ariane Szafarz, 2015. "Virtual Currency, Tangible Return: Portfolio Diversification with Bitcoins," Post-Print CEB, ULB -- Universite Libre de Bruxelles, vol. 16(6), pages 365-373.
    41. Yunus, Nafeesa, 2020. "Time-varying linkages among gold, stocks, bonds and real estate," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 165-185.
    42. Fletcher, Jonathan, 2021. "International equity U.S. mutual funds and diversification benefits," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 246-257.
    43. Sermin Gungor & Richard Luger, 2013. "Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances," Staff Working Papers 13-16, Bank of Canada.
    44. Kroencke, Tim A. & Schindler, Felix, 2012. "International diversification with securitized real estate and the veiling glare from currency risk," Journal of International Money and Finance, Elsevier, vol. 31(7), pages 1851-1866.
    45. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    46. Harry J. Turtle & Chengping Zhang, 2015. "Structural breaks and portfolio performance in global equity markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 909-922, June.
    47. Nafeesa Yunus, 2019. "Dynamic Linkages Among U.S. Real Estate Sectors Before and After the Housing Crisis," The Journal of Real Estate Finance and Economics, Springer, vol. 58(2), pages 264-289, February.
    48. Lehlohonolo Letho & Grieve Chelwa & Abdul Latif Alhassan, 2022. "Cryptocurrencies and portfolio diversification in an emerging market," China Finance Review International, Emerald Group Publishing Limited, vol. 12(1), pages 20-50, January.
    49. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2010. "Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 763-782, September.
    50. Lingfeng Li, 2003. "An Economic Measure of Diversification Benefits," Yale School of Management Working Papers ysm371, Yale School of Management, revised 01 Jul 2003.
    51. Enrique Sentana, 2008. "The Econometrics of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
    52. Fabozzi, Frank J. & Huang, Dashan & Jiang, Fuwei & Wang, Jiexun, 2024. "What difference do new factor models make in portfolio allocation?," Journal of International Money and Finance, Elsevier, vol. 140(C).
    53. Hanke, Michael & Penev, Spiridon, 2018. "Comparing large-sample maximum Sharpe ratios and incremental variable testing," European Journal of Operational Research, Elsevier, vol. 265(2), pages 571-579.
    54. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Exploring Diversification Benefits in Asia-Pacific Equity Markets," MPRA Paper 60180, University Library of Munich, Germany.
    55. Galvani, Valentina & Behnamian, Aslan, 2009. "A Comparative Analysis of the Returns on Provincial and Federal Canadian Bonds," Working Papers 2009-7, University of Alberta, Department of Economics.
    56. O'Hagan-Luff, Martha & Berrill, Jenny, 2015. "Why stay-at-home investing makes sense," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 1-14.
    57. Halil I. Memis & Steffen Sebastian, 2020. "Währungsabsicherung bei Immobilienaktien außerhalb des Euroraums [Currency hedging for real estate investments outside the Eurozone]," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 6(1), pages 47-63, April.
    58. Switzer, Lorne N. & Tahaoglu, Cagdas, 2015. "The benefits of international diversification: market development, corporate governance, market cap, and structural change effects," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 76-97.
    59. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda & Melin, Olena, 2023. "Identification-robust beta pricing, spanning, mimicking portfolios, and the benchmark neutrality of catastrophe bonds," Journal of Econometrics, Elsevier, vol. 236(1).
    60. David Ardia & S'ebastien Laurent & Rosnel Sessinou, 2024. "High-Dimensional Mean-Variance Spanning Tests," Papers 2403.17127, arXiv.org.
    61. Galvani, Valentina & Plourde, Andre, 2009. "Spanning with Zero-Price Investment Assets," Working Papers 2009-5, University of Alberta, Department of Economics.
    62. Gregor Dorfleitner & Carina Lung, 2018. "Cryptocurrencies from the perspective of euro investors: a re-examination of diversification benefits and a new day-of-the-week effect," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 472-494, December.
    63. Balli, Faruk & Balli, Hatice Ozer & Luu, Mong Ngoc, 2014. "Diversification across ASEAN-wide sectoral and national equity returns," Economic Modelling, Elsevier, vol. 41(C), pages 398-407.
    64. Ando, Masakazu & Hodoshima, Jiro, 2006. "The robustness of asset pricing models: Coskewness and cokurtosis," Finance Research Letters, Elsevier, vol. 3(2), pages 133-146, June.
    65. Nucera, Federico, 2017. "Unemployment fluctuations and the predictability of currency returns," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 88-106.
    66. Jenny Berrill & Shengkai Sun, 2018. "An Investigation into the Benefits of Investing in Chinese Multinational Companies," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 186-209, August.
    67. Lu, Qinye & Vivian, Andrew, 2020. "Domestically formed international diversification," Journal of International Money and Finance, Elsevier, vol. 103(C).
    68. Fethke, Tobias & Prokopczuk, Marcel, 2018. "Is Commodity Index Investing Profitable?," Hannover Economic Papers (HEP) dp-635, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    69. Frédéric Blanc-Brude & Timothy Whittaker & Simon Wilde, 2017. "Searching for a listed infrastructure asset class using mean–variance spanning," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(2), pages 137-179, May.
    70. Rakowski, David & Shirley, Sara, 2020. "What drives the market for exchange-traded notes?," Journal of Banking & Finance, Elsevier, vol. 111(C).
    71. Lambert, Marie & Fays, Boris & Hübner, Georges, 2020. "Factoring characteristics into returns: A clinical study on the SMB and HML portfolio construction methods," Journal of Banking & Finance, Elsevier, vol. 114(C).

  5. Raymond Kan & Guofu Zhou, 1999. "A Critique of the Stochastic Discount Factor Methodology," CEMA Working Papers 12, China Economics and Management Academy, Central University of Finance and Economics.

    Cited by:

    1. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    2. Raymond Kan & Cesare Robotti, 2006. "Specification tests of asset pricing models using excess returns," FRB Atlanta Working Paper 2006-10, Federal Reserve Bank of Atlanta.
    3. Driessen, J.J.A.G. & Melenberg, B. & Nijman, T.E., 1999. "Testing Affine Term Structure Models in Case of Transaction Costs," Discussion Paper 1999-84, Tilburg University, Center for Economic Research.
    4. Lozano, Martín & Rubio, Gonzalo, 2011. "Evaluating alternative methods for testing asset pricing models with historical data," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 136-146, January.
    5. Smith, Daniel R., 2007. "Conditional coskewness and asset pricing," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 91-119, January.
    6. Kim, Daehwan & Song, Chi-Young, 2014. "Country Fundamentals and Currency Excess Returns," East Asian Economic Review, Korea Institute for International Economic Policy, vol. 18(2), pages 111-142, June.
    7. Peter N Smith & Michael R Wickens, "undated". "Asset Pricing with Observable Stochastic Discount Factors," Discussion Papers 02/03, Department of Economics, University of York.
    8. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    9. Ahn, Seung C. & Gadarowski, Christopher, 2004. "Small sample properties of the GMM specification test based on the Hansen-Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 109-132, January.
    10. Abel, Ernest & Fletcher, Jonathan, 2004. "An empirical examination of UK emerging market unit trust performance," Emerging Markets Review, Elsevier, vol. 5(4), pages 389-408, December.
    11. Simin, Timothy, 2008. "The Poor Predictive Performance of Asset Pricing Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 355-380, June.
    12. ROCKINGER, Michael & JONDEAU, Eric, 2000. "Conditional Volatility, Skewness, and Kurtosis : Existence and Persistence," HEC Research Papers Series 710, HEC Paris.
    13. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    14. Jondeau, Eric & Rockinger, Michael, 2003. "Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements," Journal of Economic Dynamics and Control, Elsevier, vol. 27(10), pages 1699-1737, August.
    15. Wilhelm, Jochen, 2000. "Das Gaußsche Zinsstrukturmodell: Eine Analyse auf der Basis von Wahrscheinlichkeitsverteilungen," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe 6, University of Passau, Faculty of Business and Economics.
    16. Pierluigi Balduzzi & Cesare Robotti, 2005. "Mimicking portfolios, economic risk premia, and tests of multi-beta models," FRB Atlanta Working Paper 2005-04, Federal Reserve Bank of Atlanta.
    17. DeRoon, Frans A. & Nijman, Theo E., 2001. "Testing for mean-variance spanning: a survey," Journal of Empirical Finance, Elsevier, vol. 8(2), pages 111-155, May.
    18. Bartram, Söhnke M. & Bodnar, Gordon M., 2012. "Crossing the lines: The conditional relation between exchange rate exposure and stock returns in emerging and developed markets," Journal of International Money and Finance, Elsevier, vol. 31(4), pages 766-792.
    19. Ravi Jagannathan & Zhenyu Wang, 2002. "Empirical Evaluation of Asset‐Pricing Models: A Comparison of the SDF and Beta Methods," Journal of Finance, American Finance Association, vol. 57(5), pages 2337-2367, October.
    20. John H. Cochrane, 2001. "A Rehabilitation of Stochastic Discount Factor Methodology," NBER Working Papers 8533, National Bureau of Economic Research, Inc.
    21. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
    22. Ayadi, Mohamed A. & Kryzanowski, Lawrence, 2005. "Portfolio performance measurement using APM-free kernel models," Journal of Banking & Finance, Elsevier, vol. 29(3), pages 623-659, March.
    23. Massimo Guidolin & Martin Lozano & Juan Arismendi Zambrano, "undated". "Multifactor Empirical Asset Pricing Under Higher-Order Moment Variations," Economics Department Working Paper Series n304-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    24. Jay Shanken & Guofu Zhou, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," CEMA Working Papers 275, China Economics and Management Academy, Central University of Finance and Economics.
    25. Wonnho Choi, 2018. "Consumption-based capital asset pricing models: issues and controversies," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 181-205, January.
    26. Bessler, Wolfgang & Drobetz, Wolfgang & Zimmermann, Heinz, 2007. "Conditional Performance Evaluation for German Mutual Equity Funds," Working papers 2007/22, Faculty of Business and Economics - University of Basel.
    27. Khan, Mozaffar, 2008. "Are accruals mispriced Evidence from tests of an Intertemporal Capital Asset Pricing Model," Journal of Accounting and Economics, Elsevier, vol. 45(1), pages 55-77, March.
    28. Heber Farnsworth & Wayne E. Ferson & David Jackson & Steven Todd, 2002. "Performance Evaluation with Stochastic Discount Factors," NBER Working Papers 8791, National Bureau of Economic Research, Inc.
    29. Cai, Zongwu & Hong, Yongmiao, 2003. "Nonparametric Methods in Continuous-Time Finance: A Selective Review," SFB 373 Discussion Papers 2003,15, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    30. Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
    31. Guermat, Cherif & Freeman, Mark C., 2010. "A net beta test of asset pricing models," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 1-9, January.

  6. John Geweke & Guofu Zhou, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," CEMA Working Papers 276, China Economics and Management Academy, Central University of Finance and Economics.

    Cited by:

    1. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    2. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2018. "Dissecting the 2007–2009 Real Estate Market Bust: Systematic Pricing Correction or Just a Housing Fad?," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 34-62.
    3. Mr. Maxym Kryshko, 2011. "Data-Rich DSGE and Dynamic Factor Models," IMF Working Papers 2011/216, International Monetary Fund.
    4. Nobuhiko Terui & Shohei Hasegawa, 2013. "Modeling Preference Change through Brand Satiation," TMARG Discussion Papers 112, Graduate School of Economics and Management, Tohoku University.
    5. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    6. Firmin Doko Tchatoka & Nicolas Groshenny & Qazi Haque & Mark Weder, 2016. "Monetary Policy and Indeterminacy after the 2001 Slump," School of Economics and Public Policy Working Papers 2016-09, University of Adelaide, School of Economics and Public Policy.
    7. Kim, Hea-Jung & Choi, Taeryon & Jo, Seongil, 2016. "Bayesian factor analysis with uncertain functional constraints about factor loadings," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 110-128.
    8. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    9. Robert Kohn & Rachida Ouysse, 2007. "Bayesian Variable Selection of Risk Factors in the APT Model," Discussion Papers 2007-32, School of Economics, The University of New South Wales.
    10. Tsionas, Mike, 2012. "Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models," MPRA Paper 40966, University Library of Munich, Germany, revised 20 Aug 2012.
    11. Simon Beyeler & Sylvia Kaufmann, 2016. "Factor augmented VAR revisited - A sparse dynamic factor model approach," Working Papers 16.08, Swiss National Bank, Study Center Gerzensee.
    12. Massimo Guidolin & Francesco Ravazzolo & Andrea Tortora, 2014. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 49(4), pages 477-523, November.
    13. Pantelis Samartsidis & Shaun R. Seaman & Silvia Montagna & André Charlett & Matthew Hickman & Daniela De Angelis, 2020. "A Bayesian multivariate factor analysis model for evaluating an intervention by using observational time series data on multiple outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1437-1459, October.
    14. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    15. Celso Brunetti & Jeffrey H. Harris & Shawn Mankad, 2018. "Bank Holdings and Systemic Risk," Finance and Economics Discussion Series 2018-063, Board of Governors of the Federal Reserve System (U.S.).
    16. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2016. "Bayesian analysis of static and dynamic factor models: An ex-post approach towards the rotation problem," Journal of Econometrics, Elsevier, vol. 192(1), pages 190-206.
    17. Nobuhiko Terui & Shohei Hasegawa & Greg M. Allenby, 2015. "A Threshold Model for Discontinuous Preference Change and Satiation," TMARG Discussion Papers 122, Graduate School of Economics and Management, Tohoku University.
    18. Mirko Wiederholt & Emanuel Moench & Bartosz Maćkowiak, 2009. "Sectoral Price Data and Models of Price Setting," 2009 Meeting Papers 666, Society for Economic Dynamics.
    19. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2014. "Bayesian analysis of dynamic factor models: An ex-post approach towards the rotation problem," Kiel Working Papers 1902, Kiel Institute for the World Economy (IfW Kiel).
    20. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.
    21. Rodriguez, Diego & Gonzalez, Andres & Fernandez, Andres, 2015. "Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies," IDB Publications (Working Papers) 7382, Inter-American Development Bank.
    22. Nagayasu, Jun, 2015. "Global and country-specific factors in real effective exchange rates," MPRA Paper 64217, University Library of Munich, Germany.
    23. Tsung-I Lin & I-An Chen & Wan-Lun Wang, 2023. "A robust factor analysis model based on the canonical fundamental skew-t distribution," Statistical Papers, Springer, vol. 64(2), pages 367-393, April.
    24. Eric Jacquier & Nicholas G. Polson & Peter E. Rossi, 1999. "Stochastic Volatility: Univariate and Multivariate Extensions," CIRANO Working Papers 99s-26, CIRANO.
    25. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    26. Cristina Fuentes-Albero & Leonardo Melosi, 2011. "Methods for Computing Marginal Data Densities from the Gibbs Output," Departmental Working Papers 201131, Rutgers University, Department of Economics.
    27. Simon Beyeler & Sylvia Kaufmann, 2021. "Reduced‐form factor augmented VAR—Exploiting sparsity to include meaningful factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 989-1012, November.
    28. Chadwick, Meltem, 2010. "Performance of Bayesian Latent Factor Models in Measuring Pricing Errors," MPRA Paper 79060, University Library of Munich, Germany.
    29. Christian Aßmann & Jens Boysen-Hogrefe & Markus Pape, 2024. "Post-processing for Bayesian analysis of reduced rank regression models with orthonormality restrictions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 577-609, September.
    30. Roberto Tatiwa Ferreira & Herman Bierens & Ivan Castelar, 2005. "Forecasting Quarterly Brazilian GDP Growth Rate With Linear and NonLinear Diffusion Index Models," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 6(3), pages 261-292.
    31. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-1019, CIRJE, Faculty of Economics, University of Tokyo.
    32. Cederburg, Scott & O’Doherty, Michael S., 2015. "Asset-pricing anomalies at the firm level," Journal of Econometrics, Elsevier, vol. 186(1), pages 113-128.
    33. Mumtaz, Haroon & Surico, Paolo, 2008. "Evolving International Inflation Dynamics: Evidence from a Time-varying Dynamic Factor Model," CEPR Discussion Papers 6767, C.E.P.R. Discussion Papers.
    34. Christopher S. Jones & Jay Shanken, 2002. "Mutual Fund Performance with Learning Across Funds," NBER Working Papers 9392, National Bureau of Economic Research, Inc.
    35. Guohua Feng & Bin Peng & Xiaohui Zhang, 2017. "Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach," Journal of Productivity Analysis, Springer, vol. 48(2), pages 179-192, December.
    36. Klaus, Benjamin & Ferroni, Filippo, 2015. "Euro area business cycles in turbulent times: convergence or decoupling?," Working Paper Series 1819, European Central Bank.
    37. Reichmuth, Wolfgang H. & Sarferaz, Samad, 2008. "Bayesian demographic modeling and forecasting: An application to U.S. mortality," SFB 649 Discussion Papers 2008-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    38. Fernández-Villaverde, Jesús & Mineyama, Tomohide & Song, Dongho, 2024. "Are We Fragmented Yet? Measuring Geopolitical Fragmentation and Its Causal Effects," CEPR Discussion Papers 19184, C.E.P.R. Discussion Papers.
    39. Sun Jiehuan & Warren Joshua L. & Zhao Hongyu, 2017. "A Bayesian semiparametric factor analysis model for subtype identification," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(2), pages 145-158, April.
    40. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    41. Ong, Victor M.-H. & Nott, David J. & Tran, Minh-Ngoc & Sisson, Scott A. & Drovandi, Christopher C., 2018. "Likelihood-free inference in high dimensions with synthetic likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 271-291.
    42. Ouysse, Rachida & Kohn, Robert, 2010. "Bayesian variable selection and model averaging in the arbitrage pricing theory model," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3249-3268, December.
    43. Reichmuth, Wolfgang H. & Sarferaz, Samad, 2008. "Modeling and forecasting age-specific mortality: A Bayesian approach," SFB 649 Discussion Papers 2008-052a, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    44. Sylvia Kaufmann & Christian Schumacher, 2013. "Bayesian estimation of sparse dynamic factor models with order-independent identification," Working Papers 13.04, Swiss National Bank, Study Center Gerzensee.
    45. Haroon Mumtaz & Paolo Surico, 2006. "Inflation Globalization and the Fall of Country Specific Fluctuations," Computing in Economics and Finance 2006 166, Society for Computational Economics.
    46. Aßmann, Christian & Boysen-Hogrefe, Jens & Pape, Markus, 2012. "The directional identification problem in Bayesian factor analysis: An ex-post approach," Economics Working Papers 2012-11, Christian-Albrechts-University of Kiel, Department of Economics.
    47. Chen, Hong-Yi & Lee, Alice C. & Lee, Cheng-Few, 2015. "Alternative errors-in-variables models and their applications in finance research," The Quarterly Review of Economics and Finance, Elsevier, vol. 58(C), pages 213-227.
    48. Lasse Bork, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," CREATES Research Papers 2009-11, Department of Economics and Business Economics, Aarhus University.
    49. Ando, Tomohiro, 2009. "Bayesian factor analysis with fat-tailed factors and its exact marginal likelihood," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1717-1726, September.
    50. Gijsbert Suren & Guilherme Moura, 2012. "Heteroskedastic Dynamic Factor Models: A Monte Carlo Study," Economics Bulletin, AccessEcon, vol. 32(4), pages 2884-2898.
    51. Haroon Mumtaz & Alberto Musso, 2018. "The evolving impact of global, region-specific and country-specific uncertainty," Working Papers 866, Queen Mary University of London, School of Economics and Finance.
    52. Florian Eckert & Samad Sarferaz, 2019. "Agnostic Output Gap Estimation and Decomposition in Large Cross-Sections," KOF Working papers 19-467, KOF Swiss Economic Institute, ETH Zurich.
    53. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
    54. Neil Shephard & Gabriele Fiorentini & Enrique Sentana, 2003. "Likelihood-based estimation of latent generalised ARCH structures," FMG Discussion Papers dp453, Financial Markets Group.
    55. Gabriel Frahm, 0. "Arbitrage Pricing Theory In Ergodic Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(05), pages 1-28.
    56. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    57. Necati Tekatli, 2010. "A New Core Inflation Indicator for Turkey (Turkiye Ekonomisi Icin Yeni Bir Cekirdek Enflasyon Gostergesi)," Working Papers 1019, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    58. Eller, Markus & Huber, Florian & Schuberth, Helene, 2018. "How Important are Global Factors for Understanding the Dynamics of International Capital Flows?," Working Papers in Economics 2018-2, University of Salzburg.
    59. Veronika Ročková & Edward I. George, 2016. "Fast Bayesian Factor Analysis via Automatic Rotations to Sparsity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1608-1622, October.
    60. Chadi S. Abdallah & William D. Lastrapes, 2013. "Evidence on the Relationship between Housing and Consumption in the United States: A State‐Level Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 559-590, June.
    61. Massimo Guidolin & Francesco Ravazzolo & Andrea Donato Tortora, 2011. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate. Evidence from Multi-Factor Asset Pricing Models of REIT Returns," Working Papers 416, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    62. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    63. Gabriella Conti & Sylvia Frühwirth-Schnatter & James J. Heckman & Rémi Piatek, 2014. "Bayesian Exploratory Factor Analysis," NRN working papers 2014-08, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    64. Bin Peng & Giovanni Forchini, 2014. "Consistent Estimation of Panel Data Models with a Multifactor Error Structure when the Cross Section Dimension is Large," Working Paper Series 20, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    65. Geweke, John, 2003. "Econometric issues in using the AHEAD panel," Journal of Econometrics, Elsevier, vol. 112(1), pages 115-120, January.
    66. Creal, Drew & Kim, Jaeho, 2024. "Bayesian estimation of cluster covariance matrices of unknown form," Journal of Econometrics, Elsevier, vol. 241(1).
    67. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
    68. Ruben Loaiza-Maya & Didier Nibbering, 2020. "Scalable Bayesian estimation in the multinomial probit model," Papers 2007.13247, arXiv.org, revised Mar 2021.
    69. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    70. Sydney C. Ludvigson & Serena Ng, 2009. "A Factor Analysis of Bond Risk Premia," NBER Working Papers 15188, National Bureau of Economic Research, Inc.
    71. Charles S. Bos & Ronald J. Mahieu & Herman K. van Dijk, 2000. "Daily Exchange Rate Behaviour and Hedging of Currency Risk," Econometric Society World Congress 2000 Contributed Papers 0504, Econometric Society.
    72. Philip A. White & Alan E. Gelfand, 2021. "Multivariate functional data modeling with time-varying clustering," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 586-602, September.
    73. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
    74. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    75. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    76. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    77. Vitoratou, Silia & Ntzoufras, Ioannis & Moustaki, Irini, 2016. "Explaining the behavior of joint and marginal Monte Carlo estimators in latent variable models with independence assumptions," LSE Research Online Documents on Economics 57685, London School of Economics and Political Science, LSE Library.
    78. Michailidis, G., 2009. "Multivariate methods in examining macroeconomic variables effect on Greek stock market returns, 1997-2004," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    79. Necati Tekatli, 2007. "Generalized Factor Models: A Bayesian Approach," Working Papers 334, Barcelona School of Economics.
    80. Terrance Savitsky & Daniel McCaffrey, 2014. "Bayesian Hierarchical Multivariate Formulation with Factor Analysis for Nested Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 275-302, April.
    81. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2015. "Capturing the Impact of Unobserved Sector-Wide Shocks on Stock Returns with Panel Data Model," The Economic Record, The Economic Society of Australia, vol. 91(295), pages 495-508, December.
    82. Zhou, Guofu, 1999. "Security factors as linear combinations of economic variables," Journal of Financial Markets, Elsevier, vol. 2(4), pages 403-432, November.
    83. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
    84. László Békési & Lorant Kaszab & Szabolcs Szentmihályi, 2017. "The EAGLE model for Hungary - a global perspective," MNB Working Papers 2017/7, Magyar Nemzeti Bank (Central Bank of Hungary).
    85. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
    86. Christensen, Bent Jesper & van der Wel, Michel, 2019. "An asset pricing approach to testing general term structure models," Journal of Financial Economics, Elsevier, vol. 134(1), pages 165-191.
    87. Manuel Ammann & Michael Verhofen, 2008. "Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach," European Financial Management, European Financial Management Association, vol. 14(3), pages 391-418, June.
    88. Sylvia Frühwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When It Counts—Econometric Identification of the Basic Factor Model Based on GLT Structures," Econometrics, MDPI, vol. 11(4), pages 1-30, November.
    89. Joshua Chan & Eric Eisenstat & Xuewen Yu, 2022. "Large Bayesian VARs with Factor Stochastic Volatility: Identification, Order Invariance and Structural Analysis," Papers 2207.03988, arXiv.org.
    90. Leung, Dennis & Drton, Mathias, 2016. "Order-invariant prior specification in Bayesian factor analysis," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 60-66.
    91. Mohamed Saidane & Christian Lavergne, 2007. "A structured variational learning approach for switching latent factor models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(3), pages 245-268, October.
    92. Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
    93. Roberta De Vito & Ruggero Bellio & Lorenzo Trippa & Giovanni Parmigiani, 2019. "Multi‐study factor analysis," Biometrics, The International Biometric Society, vol. 75(1), pages 337-346, March.
    94. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2023. "General Bayesian time‐varying parameter vector autoregressions for modeling government bond yields," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 69-87, January.
    95. Tibor Szendrei & Katalin Varga, 2017. "FISS - A Factor Based Index of Systemic Stress in the Financial System," MNB Working Papers 2017/9, Magyar Nemzeti Bank (Central Bank of Hungary).
    96. Shakouri, Hamed & Pandey, Shikhar & Rahmatian, Farnoosh & Paaso, Esa A., 2023. "Does the increased electricity consumption (provided by capacity expansion and/or reliability improvement) cause economic growth?," Energy Policy, Elsevier, vol. 182(C).
    97. Edward P. Herbst & Fabian Winkler, 2021. "The Factor Structure of Disagreement," Finance and Economics Discussion Series 2021-046, Board of Governors of the Federal Reserve System (U.S.).
    98. Xiaoyi Han & Lung-Fei Lee, 2016. "Bayesian Analysis of Spatial Panel Autoregressive Models With Time-Varying Endogenous Spatial Weight Matrices, Common Factors, and Random Coefficients," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 642-660, October.
    99. Calzolari, Giorgio & Halbleib, Roxana, 2018. "Estimating stable latent factor models by indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 280-301.
    100. Kim Sawyer & André Gygax & Matthew Hazledine, 2010. "Pricing errors and estimates of risk premia in factor models," Annals of Finance, Springer, vol. 6(3), pages 391-403, July.
    101. Nagayasu, Jun, 2016. "Commonality and Heterogeneity in Real Effective Exchange Rates: Evidence from Advanced and Developing Countries," MPRA Paper 70078, University Library of Munich, Germany.
    102. Zura Kakushadze & Willie Yu, 2018. "Betas, Benchmarks and Beating the Market," Papers 1807.09919, arXiv.org.
    103. Elena A. Erosheva & S. McKay Curtis, 2017. "Dealing with Reflection Invariance in Bayesian Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 295-307, June.
    104. Sakae Oya & Teruo Nakatsuma, 2021. "Identification in Bayesian Estimation of the Skewness Matrix in a Multivariate Skew-Elliptical Distribution," Papers 2108.04019, arXiv.org.
    105. Javier Maldonado & Esther Ruiz, 2021. "Accurate Confidence Regions for Principal Components Factors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1432-1453, December.
    106. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    107. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    108. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    109. Necati Tekatli, 2010. "A Bayesian Generalized Factor Model with Comparative Analysis (Genellestirilmis Faktor Modellerinin Bayesyen Yaklasimi ve Karsilastirmali Analizi)," Working Papers 1018, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    110. Kohn, Robert & Nguyen, Nghia & Nott, David & Tran, Minh-Ngoc, 2017. "Random Effects Models with Deep Neural Network Basis Functions: Methodology and Computation," Working Papers 2123/17877, University of Sydney Business School, Discipline of Business Analytics.
    111. Kaufmann, Sylvia & Schumacher, Christian, 2019. "Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification," Journal of Econometrics, Elsevier, vol. 210(1), pages 116-134.
    112. Harding, Matthew C., 2008. "Explaining the single factor bias of arbitrage pricing models in finite samples," Economics Letters, Elsevier, vol. 99(1), pages 85-88, April.
    113. Mário Jorge Mendonça & Cláudio Hamilton dos Santos & Thiago Guerrera Martins, 2009. "Aplicação de um Modelo Fatorial Dinâmico Para Previsão da Arrecadação Tributária no Brasil," Discussion Papers 1453, Instituto de Pesquisa Econômica Aplicada - IPEA.
    114. Carel Peeters, 2012. "Rotational Uniqueness Conditions Under Oblique Factor Correlation Metric," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 288-292, April.
    115. Roger S. Zoh & Bani Mallick & Ivan Ivanov & Veera Baladandayuthapani & Ganiraju Manyam & Robert S. Chapkin & Johanna W. Lampe & Raymond J. Carroll, 2016. "PCAN: Probabilistic correlation analysis of two non‐normal data sets," Biometrics, The International Biometric Society, vol. 72(4), pages 1358-1368, December.
    116. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    117. Brechmann, Eike C. & Joe, Harry, 2014. "Parsimonious parameterization of correlation matrices using truncated vines and factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 233-251.
    118. KiHoon Jimmy Hong & Bin Peng & Xiaohui Zhang, 2014. "Capturing the Impact of Latent Industry-Wide Shocks with Dynamic Panel Model," Research Paper Series 347, Quantitative Finance Research Centre, University of Technology, Sydney.
    119. Sylvia Kaufmann & Markus Pape, 2023. "Bayesian (non-)unique sparse factor modelling," Working Papers 23.04, Swiss National Bank, Study Center Gerzensee.
    120. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.
    121. Chu Zhang, 2009. "Testing the APT with the Maximum Sharpe Ratio of Extracted Factors," Management Science, INFORMS, vol. 55(7), pages 1255-1266, July.
    122. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.

  7. Campbell R. Harvey & Guofu Zhou, 1993. "International asset pricing with alternative distributional specifications," CEMA Working Papers 277, China Economics and Management Academy, Central University of Finance and Economics.

    Cited by:

    1. Radosław Kurach, 2013. "Does Beta Explain Global Equity Market Volatility – Some Empirical Evidence," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(2), June.
    2. Guorui Bian & Michael McAleer & Wing-Keung Wong, 2012. "Robust Estimation and Forecasting of the Capital Asset Pricing Model," Documentos de Trabajo del ICAE 2012-09, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2012.
    3. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    4. Chou, Pin-Huang, 1997. "A Gibbs sampling approach to the estimation of linear regression models under daily price limits," Pacific-Basin Finance Journal, Elsevier, vol. 5(1), pages 39-62, February.
    5. Massimo Guidolin & Allan Timmermann, 2008. "International asset allocation under regime switching, skew, and kurtosis preferences," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 889-935, April.
    6. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
    7. Schneider, Martin & Albuquerque, Rui & Bauer, Gregory, 2005. "International Equity Flows and Returns: A Quantitative Equilibrium Approach," CEPR Discussion Papers 5159, C.E.P.R. Discussion Papers.
    8. Mauleon, Ignacio, 2003. "Financial densities in emerging markets: an application of the multivariate ES density," Emerging Markets Review, Elsevier, vol. 4(2), pages 197-223, June.
    9. Yuenan Wang & Amalia Di Iorio, 2007. "The cross-sectional relationship between stock returns and domestic and global factors in the Chinese A-share market," Review of Quantitative Finance and Accounting, Springer, vol. 29(2), pages 181-203, August.
    10. Boyd, John H. & Jalal, Abu M., 2012. "A new measure of financial development: Theory leads measurement," Journal of Development Economics, Elsevier, vol. 99(2), pages 341-357.
    11. Joaquim Pinto de Andrade & Vladimir Kuhl Teles, 2004. "An Empirical Model of the Brazilian Country Risk - An Extension of the Beta Country Risk Model," Econometric Society 2004 Latin American Meetings 284, Econometric Society.
    12. Teles, Vladimir Kühl & Andrade, Joaquim Pinto de, 2010. "Monetary policy and country risk," Textos para discussão 223, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    13. Basher, Syed A. & Sadorsky, Perry, 2006. "Oil price risk and emerging stock markets," Global Finance Journal, Elsevier, vol. 17(2), pages 224-251, December.
    14. Adam Zaremba, 2019. "The Cross Section of Country Equity Returns: A Review of Empirical Literature," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    15. Gerard, Bruno & Thanyalakpark, Kessara & Batten, Jonathan A., 2003. "Are the East Asian markets integrated? Evidence from the ICAPM," Journal of Economics and Business, Elsevier, vol. 55(5-6), pages 585-607.
    16. Stephen Anthony & Hamid Yahyaei, 2022. "Bringing Credibility Back to Macroeconomic Policy Frameworks," Economic Papers, The Economic Society of Australia, vol. 41(3), pages 276-295, September.
    17. R. D. Brooks & R. W. Faff & M. McKenzie, 2002. "Time varying country risk: an assessment of alternative modelling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 249-274.
    18. Gangemi, Michael A. M. & Brooks, Robert D. & Faff, Robert W., 2000. "Modeling Australia's country risk: a country beta approach," Journal of Economics and Business, Elsevier, vol. 52(3), pages 259-276.
    19. James Sfiridis & Alan Gelfand, 2002. "A survey of sampling-based Bayesian analysis of financial data," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(4), pages 273-291.
    20. Fletcher, Jonathan, 2000. "On the conditional relationship between beta and return in international stock returns," International Review of Financial Analysis, Elsevier, vol. 9(3), pages 235-245.
    21. Gangemi, Michael & Brooks, Robert & Faff, Robert, 1999. "Mean reversion and the forecasting of country betas: a note," Global Finance Journal, Elsevier, vol. 10(2), pages 231-245.
    22. Jacobsen, Brian J. & Liu, Xiaochun, 2008. "China's segmented stock market: An application of the conditional international capital asset pricing model," Emerging Markets Review, Elsevier, vol. 9(3), pages 153-173, September.
    23. Bee-Hoong Tay & Pei-Tha Gan, 2016. "The Determinants of Investment Rewards: Evidence for Selected Developed and Developing Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1180-1188.
    24. Hammami Algia & Bouri Abdelfatteh, 2018. "The Conditional Relationship between Oil Price Risk and Return Stock Market: a Comparative Study of Advanced and Emerging Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(4), pages 1321-1347, December.
    25. Mr. Fabian Lipinsky & Ms. Li L Ong, 2014. "Asia’s Stock Markets: Are There Crouching Tigers and Hidden Dragons?," IMF Working Papers 2014/037, International Monetary Fund.
    26. Mika Vaihekoski, 2000. "Unconditional international asset pricing models: empirical tests," Finnish Economic Papers, Finnish Economic Association, vol. 13(2), pages 71-88, Autumn.
    27. Hueng, C. James, 2014. "Are global systematic risk and country-specific idiosyncratic risk priced in the integrated world markets?," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 28-38.
    28. Robert Brooks & Robert Faff & David Sokulsky, 2005. "The stock market impact of German reunification: international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 15(1), pages 31-42.
    29. Wing-Keung Wong & Guorui Bian, 2005. "Robust Estimation of Multiple Regression Model with Non-normal Error: Symmetric Distribution," Monash Economics Working Papers 09/05, Monash University, Department of Economics.
    30. Raymond Kan & Guofu Zhou, 1999. "A Critique of the Stochastic Discount Factor Methodology," CEMA Working Papers 12, China Economics and Management Academy, Central University of Finance and Economics.
    31. Chen, Rongda & Yu, Lean, 2013. "A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions," Economic Modelling, Elsevier, vol. 35(C), pages 796-804.
    32. Mr. Luis Catão & Mr. Allan Timmermann, 2003. "Country and Industry Dynamics in Stock Returns," IMF Working Papers 2003/052, International Monetary Fund.
    33. González, M. & Minguez, R., 2005. "The Method Of Simulated Maximum Likelihood For The Estimaton Of Dynamic Ordered Probit: An Application To Country-Risk For Non-Developed Countries," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(3), pages 99-133.
    34. Francesco Giurda & Elias Tzavalis, 2004. "Is the Currency Risk Priced in Equity Markets?," Working Papers 511, Queen Mary University of London, School of Economics and Finance.
    35. Brooks, Robert & Faff, Robert W. & Hillier, David & Hillier, Joseph, 2004. "The national market impact of sovereign rating changes," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 233-250, January.
    36. Humberto Valencia-Herrera & Francisco López-Herrera, 2018. "Markov Switching International Capital Asset Pricing Model, an Emerging Market Case: Mexico," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(1), pages 96-129, April.
    37. Rui Albuquerque & Gregory Bauer & Martin Schneider, 2004. "Characterizing Asymmetric Information in International Equity Markets," International Finance 0405005, University Library of Munich, Germany.
    38. Shyh-Wei Chen & Nai-Chuan Huang, 2007. "Estimates of the ICAPM with regime-switching betas: evidence from four pacific rim economies," Applied Financial Economics, Taylor & Francis Journals, vol. 17(4), pages 313-327.
    39. Frida Lie & Robert Faff, 2003. "Global industry betas," Applied Economics Letters, Taylor & Francis Journals, vol. 10(1), pages 21-26.
    40. William Shambora & Shamila Jayasuriya, 2008. "The world is shrinking: Evidence for stock market convergence," Economics Bulletin, AccessEcon, vol. 7(14), pages 1-12.
    41. Robert Brooks & Xibin Zhang & Emawtee Bissoondoyal Bheenick, 2007. "Country risk and the estimation of asset return distributions," Quantitative Finance, Taylor & Francis Journals, vol. 7(3), pages 261-265.
    42. Jay Shanken & Guofu Zhou, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," CEMA Working Papers 275, China Economics and Management Academy, Central University of Finance and Economics.
    43. Saleem, Kashif & Vaihekoski, Mika, 2007. "Time-varying global and local sources of risk in Russian stock market," MPRA Paper 5787, University Library of Munich, Germany.
    44. Chopra, Parvesh K. & Kanji, Gopal K., 2010. "On Measuring Country Risk: A new System Modelling Approach - La misura del rischio paese: un nuovo approccio system modelling," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 63(4), pages 479-515.
    45. Benson, Karen L. & Faff, Robert W., 2006. "Conditional performance evaluation and the relevance of money flows for Australian international equity funds," Pacific-Basin Finance Journal, Elsevier, vol. 14(3), pages 231-249, June.
    46. Velu, Raja & Zhou, Guofu, 1999. "Testing multi-beta asset pricing models," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 219-241, September.
    47. Utpal Bhattacharya & Hazem Daouk, 2002. "The World Price of Insider Trading," Journal of Finance, American Finance Association, vol. 57(1), pages 75-108, February.
    48. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
    49. Rahul Verma & Priti Verma, 2005. "Do Emerging Equity Markets Respond Symmetrically to US Market Upturns and Downturns? Evidence from Latin America," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 4(3), pages 193-208, December.
    50. Majumder, Debasish, 2014. "Asset pricing for inefficient markets: Evidence from China and India," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 282-291.
    51. Antell, Jan & Vaihekoski, Mika, 2007. "International asset pricing models and currency risk: Evidence from Finland 1970-2004," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2571-2590, September.
    52. Verma, Rahul & Soydemir, Gokce, 2006. "Modeling country risk in Latin America: A country beta approach," Global Finance Journal, Elsevier, vol. 17(2), pages 192-213, December.
    53. Ülkü, Numan & Baker, Saleh, 2014. "Country world betas: The link between the stock market beta and macroeconomic beta," Finance Research Letters, Elsevier, vol. 11(1), pages 36-46.
    54. Manuel Galea & David Cademartori & Roberto Curci & Alonso Molina, 2020. "Robust Inference in the Capital Asset Pricing Model Using the Multivariate t -distribution," JRFM, MDPI, vol. 13(6), pages 1-22, June.
    55. Guermat, Cherif & Freeman, Mark C., 2010. "A net beta test of asset pricing models," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 1-9, January.

Articles

  1. Han, Yufeng & Huang, Dashan & Huang, Dayong & Zhou, Guofu, 2022. "Expected return, volume, and mispricing," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1295-1315.

    Cited by:

    1. Li, Wencong & Yang, Xingquan & Yin, Xingqiang, 2022. "Non-state shareholders entering of state-owned enterprises and equity mispricing: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Li, Yan & Liang, Chao & Huynh, Toan L.D. & He, Qiubei, 2022. "Price reversal and heterogeneous belief," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 104-119.
    3. Sun, Kaisi & Wang, Hui & Zhu, Yifeng, 2023. "Salience theory in price and trading volume: Evidence from China," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 38-61.
    4. Hou, Yuting & Jin, Xiu, 2024. "Downside liquidity risk premium: From the perspective of higher moment," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    5. Luu, Ellie & Xu, Fangming & Zheng, Liyi, 2023. "Short-selling activities in the time of COVID-19," The British Accounting Review, Elsevier, vol. 55(4).
    6. Du, Xiaoxu & Tang, Zhenpeng & Chen, Kaijie, 2023. "A novel crude oil futures trading strategy based on volume-price time-frequency decomposition with ensemble deep reinforcement learning," Energy, Elsevier, vol. 285(C).
    7. Ao, Zhiming & Ji, Xinru & Liang, Xinxin, 2023. "Can prospect theory explain anomalies in the Chinese stock market?," Finance Research Letters, Elsevier, vol. 58(PB).
    8. Chen, Xin & Chai, Daniel & Zhang, Jin, 2024. "Expected return, volume, and mispricing: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    9. Fang, Yi & Niu, Hui & Lin, Yuen, 2023. "Ex-ante Valuation based on Prospect Theory," MPRA Paper 116386, University Library of Munich, Germany.
    10. Lin, Xudong & Zhu, Hao & Meng, Yiqun, 2023. "ESG greenwashing and equity mispricing: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PD).
    11. Han, Chunmao & Zhang, Wei, 2024. "Trading volume, anomaly returns and noise trader risk in China," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).

  2. Liu, Hong & Tang, Xiaoxiao & Zhou, Guofu, 2022. "Recovering the FOMC risk premium," Journal of Financial Economics, Elsevier, vol. 145(1), pages 45-68.

    Cited by:

    1. Juan M. Londono & Mehrdad Samadi, 2023. "The Price of Macroeconomic Uncertainty: Evidence from Daily Options," International Finance Discussion Papers 1376, Board of Governors of the Federal Reserve System (U.S.).
    2. Zhang, Chu & Zhao, Shen, 2023. "The macroeconomic announcement premium and information environment," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 55-73.
    3. Kiriu, Takuya & Hibiki, Norio, 2024. "The impact of macroeconomic announcements on risk, preference, and risk premium," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 842-857.

  3. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.

    Cited by:

    1. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    2. Efstathios Polyzos & Ghulame Rubbaniy & Mieszko Mazur, 2024. "Efficient Market Hypothesis on the blockchain: A social‐media‐based index for cryptocurrency efficiency," The Financial Review, Eastern Finance Association, vol. 59(3), pages 807-829, August.
    3. Dohyun Chun & Jongho Kang & Jihun Kim, 2024. "Forecasting returns with machine learning and optimizing global portfolios: evidence from the Korean and U.S. stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-30, December.
    4. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    5. Hsiu-Chuan Lee & Donald Lien & Her-Jiun Sheu, 2023. "Hedging performance of volatility index futures: a partial cointegration approach," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 265-294, July.
    6. Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2024. "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper 2022-16b, Federal Reserve Bank of Atlanta.
    7. Lee, Hsiu-Chuan & Lee, Yun-Huan & Nguyen, Cuong, 2023. "Tail comovements of implied volatility indices and global index futures returns predictability," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    9. Sudarshan Kumar & Sobhesh Kumar Agarwalla & Jayanth R. Varma & Vineet Virmani, 2023. "Harvesting the volatility smile in a large emerging market: A Dynamic Nelson–Siegel approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1615-1644, November.
    10. Yonghe Lu & Yanrong Yang & Terry Zhang, 2024. "Double Descent in Portfolio Optimization: Dance between Theoretical Sharpe Ratio and Estimation Accuracy," Papers 2411.18830, arXiv.org.
    11. Zhu, Lin & Jiang, Fuwei & Tang, Guohao & Jin, Fujing, 2024. "From macro to micro: Sparse macroeconomic risks and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    12. Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
    13. Hanauer, Matthias X. & Jansen, Maarten & Swinkels, Laurens & Zhou, Weili, 2024. "Factor models for Chinese A-shares," International Review of Financial Analysis, Elsevier, vol. 91(C).
    14. Bryan Kelly & Semyon Malamud & Kangying Zhou, 2024. "The Virtue of Complexity in Return Prediction," Journal of Finance, American Finance Association, vol. 79(1), pages 459-503, February.
    15. Tian Ma & Cunfei Liao & Fuwei Jiang, 2023. "Timing the factor zoo via deep learning: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 485-505, March.
    16. Kuppenheimer, Gregory & Shelly, Stuart & Strauss, Jack, 2023. "Can machine learning identify sector-level financial ratios that predict sector returns?," Finance Research Letters, Elsevier, vol. 57(C).
    17. Shi, Yongdong & Wang, Haomiao & Xia, Yu & Zhen, Hongxian, 2023. "Mispricing and anomalies in China," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    18. Kim Long Tran & Hoang Anh Le & Cap Phu Lieu & Duc Trung Nguyen, 2023. "Machine Learning to Forecast Financial Bubbles in Stock Markets: Evidence from Vietnam," IJFS, MDPI, vol. 11(4), pages 1-18, November.
    19. Jozef Barunik & Martin Hronec & Ondrej Tobek, 2024. "Predicting the distributions of stock returns around the globe in the era of big data and learning," Papers 2408.07497, arXiv.org.
    20. Nygaard, Knut & Sørensen, Lars Qvigstad, 2024. "Betting on war? Oil prices, stock returns, and extreme geopolitical events," Energy Economics, Elsevier, vol. 136(C).
    21. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    22. Fabian Hollstein & Marcel Prokopczuk, 2023. "Managing the Market Portfolio," Management Science, INFORMS, vol. 69(6), pages 3675-3696, June.
    23. Nusret Cakici & Christian Fieberg & Daniel Metko & Adam Zaremba, 2024. "Do Anomalies Really Predict Market Returns? New Data and New Evidence," Review of Finance, European Finance Association, vol. 28(1), pages 1-44.
    24. Du, Qingjie & Wang, Yang & Wei, Chishen & Wei, K.C. John, 2023. "Machine learning, anomalies, and the expected market return: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    25. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    26. Ma, Tian & Liao, Cunfei & Jiang, Fuwei, 2024. "Factor momentum in the Chinese stock market," Journal of Empirical Finance, Elsevier, vol. 75(C).
    27. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).

  4. Huang, Dashan & Li, Jiangyuan & Wang, Liyao & Zhou, Guofu, 2020. "Time series momentum: Is it there?," Journal of Financial Economics, Elsevier, vol. 135(3), pages 774-794.

    Cited by:

    1. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    2. Onishchenko, Olena & Zhao, Jing & Kongahawatte, Sampath & Kuruppuarachchi, Duminda, 2024. "Investor heterogeneity and anchoring-induced momentum," Journal of Behavioral and Experimental Finance, Elsevier, vol. 42(C).
    3. Guijin Son & Hanwool Lee & Nahyeon Kang & Moonjeong Hahm, 2023. "Removing Non-Stationary Knowledge From Pre-Trained Language Models for Entity-Level Sentiment Classification in Finance," Papers 2301.03136, arXiv.org, revised Jan 2023.
    4. Markus Sihvonen, 2024. "Yield curve momentum," Review of Finance, European Finance Association, vol. 28(3), pages 805-830.
    5. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2019. "Return Signal Momentum," QBS Working Paper Series 2019/04, Queen's University Belfast, Queen's Business School.
    6. Schmeling, Maik & Medhat, Mamdouh, 2021. "Short-term Momentum," CEPR Discussion Papers 15857, C.E.P.R. Discussion Papers.
    7. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2021. "Investor heterogeneity and momentum-based trading strategies in China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    8. Zhang, Zhehao & Xing, Ruina & Liu, Jiajun & Shao, Yifei, 2023. "Correlation-based investment strategies: A comparison between Chinese and US stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    9. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    10. Sommerfeldt, Nelson & Pearce, Joshua M., 2023. "Can grid-tied solar photovoltaics lead to residential heating electrification? A techno-economic case study in the midwestern U.S," Applied Energy, Elsevier, vol. 336(C).
    11. Yufeng Han & Lingfei Kong, 2022. "A trend factor in commodity futures markets: Any economic gains from using information over investment horizons?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 803-822, May.
    12. Zhang, Junting & Liu, Haifei & Bai, Wei & Li, Xiaojing, 2024. "A hybrid approach of wavelet transform, ARIMA and LSTM model for the share price index futures forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    13. Zhenya Liu & Shanglin Lu & Shixuan Wang, 2021. "Asymmetry, tail risk and time series momentum," Post-Print hal-03511436, HAL.
    14. Sina Ehsani & Juhani T. Linnainmaa, 2022. "Factor Momentum and the Momentum Factor," Journal of Finance, American Finance Association, vol. 77(3), pages 1877-1919, June.
    15. Tobias Wiest, 2023. "Momentum: what do we know 30 years after Jegadeesh and Titman’s seminal paper?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(1), pages 95-114, March.
    16. Zhang, Yu & Kappou, Konstantina & Urquhart, Andrew, 2024. "Macroeconomic momentum and cross-sectional equity market indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    17. Hutchinson, Mark C. & Kyziropoulos, Panagiotis E. & O'Brien, John & O'Reilly, Philip & Sharma, Tripti, 2022. "Are carry, momentum and value still there in currencies?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    18. Kai Biehl & Franziska Disslbacher & Michael Ertl & Georg Feigl & Julia Hofmann & Markus Marterbauer & Patrick Mokre & Reinhold Russinger & Matthias Schnetzer & Jana Schultheiss & Tobias Schweitzer & T, 2020. "Der österreichische Sozialstaat in der Covid-19-Krise," Wirtschaft und Gesellschaft - WuG, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik, vol. 46(4), pages 487-500.
    19. Zhang, Wei & Wang, Pengfei & Li, Yi, 2021. "Bond intraday momentum," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    20. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    21. Zhong, Hao & He, Xiaoxiao & Li, Yuqi, 2024. "Is there a time-series momentum effect in the Asian crude oil futures market?," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    22. Simarjeet Singh & Nidhi Walia & Sivagandhi Saravanan & Preeti Jain & Avtar Singh & Jinesh jain, 2021. "Mapping the scientific research on alternative momentum investing: a bibliometric analysis," Journal of Economic and Administrative Sciences, Emerald Group Publishing Limited, vol. 38(4), pages 619-636, April.
    23. Zhang, Shaojun, 2022. "Dissecting currency momentum," Journal of Financial Economics, Elsevier, vol. 144(1), pages 154-173.
    24. Gao, Ya & Guo, Bin & Xiong, Xiong, 2021. "Signed momentum in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    25. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Economics Discussion Papers em-dp2022-10, Department of Economics, University of Reading.
      • Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    26. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.
    27. Fan, Minyou & Kearney, Fearghal & Li, Youwei & Liu, Jiadong, 2020. "Momentum and the Cross-Section of Stock Volatility," QBS Working Paper Series 2020/01, Queen's University Belfast, Queen's Business School.
    28. Rüdiger Weber & Annika Weber & Christine Laudenbach & Johannes Wohlfart, 2021. "Beliefs About the Stock Market and Investment Choices: Evidence from a Field Experiment," CEBI working paper series 21-17, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    29. Goulding, Christian L. & Harvey, Campbell R. & Mazzoleni, Michele G., 2023. "Momentum turning points," Journal of Financial Economics, Elsevier, vol. 149(3), pages 378-406.
    30. Minyou Fan & Youwei Li & Ming Liao & Jiadong Liu, 2022. "A reexamination of factor momentum: How strong is it?," The Financial Review, Eastern Finance Association, vol. 57(3), pages 585-615, August.
    31. Zakamulin, Valeriy & Giner, Javier, 2022. "Time series momentum in the US stock market: Empirical evidence and theoretical analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
    32. Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
    33. Simarjeet Singh & Nidhi Walia & Stelios Bekiros & Arushi Gupta & Jigyasu Kumar & Amar Kumar Mishra, 2022. "Risk-managed time-series momentum: an emerging economy experience," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, vol. 27(54), pages 328-343, November.
    34. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    35. Islam, M.S. & Das, Barun K. & Das, Pronob & Rahaman, Md Habibur, 2021. "Techno-economic optimization of a zero emission energy system for a coastal community in Newfoundland, Canada," Energy, Elsevier, vol. 220(C).
    36. Koziol, Christian & Proelss, Juliane, 2021. "An explanation for momentum with a rational model under symmetric information – Evidence from cross country equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    37. Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023. "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 54-77.
    38. Blanco, Ivan & De Jesus, Miguel & Remesal, Alvaro, 2023. "Overlapping momentum portfolios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 1-22.
    39. Borgards, Oliver, 2021. "Dynamic time series momentum of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    40. Quanbiao Shang & Teresa Serra & Philip Garcia, 2023. "Ride the trend: Is there spread momentum profit in the US commodity markets?," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(1), pages 24-47, February.
    41. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    42. Ma, Tian & Liao, Cunfei & Jiang, Fuwei, 2024. "Factor momentum in the Chinese stock market," Journal of Empirical Finance, Elsevier, vol. 75(C).
    43. Ming, Lei & Song, Wuqi & Dong, Minyi, 2023. "Revisiting time series momentum in China's commodity futures market: Evidence on sources of momentum profits," Economic Modelling, Elsevier, vol. 128(C).
    44. Christine Laudenbach & Annika Weber & Johannes Wohlfart, 2021. "Beliefs About the Stock Market and Investment Choices: Evidence from a Field Experiment," ECONtribute Discussion Papers Series 128, University of Bonn and University of Cologne, Germany.

  5. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.

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    2. Gric, Zuzana & Bajzík, Josef & Badura, Ondřej, 2023. "Does sentiment affect stock returns? A meta-analysis across survey-based measures," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    4. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    5. Chen, Shaoling & Gao, Qing & Peng, Qing & Yang, Haisheng, 2021. "Government-decentralized power: Measurement and effects," Emerging Markets Review, Elsevier, vol. 48(C).
    6. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    7. Yin, Libo & Nie, Jing, 2021. "Adjusted dividend-price ratios and stock return predictability: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 73(C).
    8. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    9. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    10. Prajwal Eachempati & Praveen Ranjan Srivastava, 2021. "Accounting for unadjusted news sentiment for asset pricing," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 13(3), pages 383-422, May.
    11. John L. Campbell & Hye Seung “Grace” Lee & Hsin‐Min Lu & Logan B. Steele, 2020. "Express Yourself: Why Managers' Disclosure Tone Varies Across Time and What Investors Learn From It," Contemporary Accounting Research, John Wiley & Sons, vol. 37(2), pages 1140-1171, June.
    12. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
    13. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    14. Song, Ziyu & Gong, Xiaomin & Zhang, Cheng & Yu, Changrui, 2023. "Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 528-545.
    15. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    16. Mathur, Aakriti & Sengupta, Rajeswari & Pratap, Bhanu, 2024. "Equity market responses to surprise Covid-19 lockdowns: The role of pandemic-driven uncertainty," Journal of Asian Economics, Elsevier, vol. 91(C).
    17. Yaojie Zhang & Qingxiang Han & Mengxi He, 2024. "Forecasting stock market returns with a lottery index: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1595-1606, August.
    18. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    19. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021. "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers 202118, University of Pretoria, Department of Economics.
    20. He, Yu & Lu, Shanglin & Wei, Ran & Wang, Shixuan, 2024. "Local media sentiment towards pollution and its effect on corporate green innovation," International Review of Financial Analysis, Elsevier, vol. 94(C).
    21. Ding Du & Ou Hu, 2020. "Why does stock-market investor sentiment influence corporate investment?," Review of Quantitative Finance and Accounting, Springer, vol. 54(4), pages 1221-1246, May.
    22. Xu, Yongan & Liang, Chao & Wang, Jianqiong, 2023. "Financial stress and returns predictability: Fresh evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    23. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    24. Apergis, Nicholas, 2022. "Overconfidence and US stock market returns," Finance Research Letters, Elsevier, vol. 45(C).
    25. Dashan Huang & Jiangyuan Li & Liyao Wang & Guofu Zhou, 2020. "Time series momentum: Is it there?," CEMA Working Papers 717, China Economics and Management Academy, Central University of Finance and Economics.
    26. Jiang, Dequan & Li, Weiping & Shen, Yongjian & Yu, Shuangli, 2022. "Does air pollution affect earnings management? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    27. Shuangyan Li & Guangrui Wang & Yongli Luo, 2022. "Tone of language, financial disclosure, and earnings management: a textual analysis of form 20-F," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    28. Haykel Tlili & Kais Tissaoui & Bassem Kahouli & Rabab Triki, 2024. "How volatility in the oil market and uncertainty shocks affect Saudi economy: a frequency approach," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-24, December.
    29. Chen, Jian & Qi, Shuyuan, 2024. "Limit-hitting exciting effects: Modeling jump dependencies in stock markets adhering to daily price-limit rules," Journal of Banking & Finance, Elsevier, vol. 163(C).
    30. Antonio Gargano & Juan Sotes-Paladino & Patrick Verwijmeren, 2022. "Out of Sync: Dispersed Short Selling and the Correction of Mispricing," Working Papers 108, Red Nacional de Investigadores en Economía (RedNIE).
    31. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    32. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    33. Aakriti Mathur & Rajeswari Sengupta & Bhanu Pratap, 2022. "Saved by the bell? Equity market responses to surprise Covid-19 lockdowns and central bank interventions," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2022-001, Indira Gandhi Institute of Development Research, Mumbai, India.
    34. Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023. "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, vol. 125(C).
    35. Zhuo Huang & Fang Liang & Chen Tong, 2021. "The predictive power of macroeconomic uncertainty for commodity futures volatility," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 989-1012, September.
    36. Aktas, Nihat & Boone, Audra & Croci, Ettore & Signori, Andrea, 2021. "Reductions in CEO career horizons and corporate policies," Journal of Corporate Finance, Elsevier, vol. 66(C).
    37. Manish Jha & Jialin Qian & Michael Weber & Baozhong Yang, 2024. "ChatGPT and Corporate Policies," NBER Working Papers 32161, National Bureau of Economic Research, Inc.
    38. Feng, Guo & Tang, Bo & Wen, Jipeng & Yan, Shuo, 2022. "The effect on stock performance of executives' emotions during IPO roadshows," International Review of Financial Analysis, Elsevier, vol. 81(C).
    39. Xiaojun Chu & Jianying Qiu, 2021. "Forecasting stock returns using first half an hour order imbalance," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3236-3245, July.
    40. Samuel YM Ze‐To, 2022. "Fundamental index aligned and excess market return predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 592-614, April.
    41. Xu, Yongan & Duong, Duy & Xu, Hualong, 2023. "Attention! Predicting crude oil prices from the perspective of extreme weather," Finance Research Letters, Elsevier, vol. 57(C).
    42. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    43. Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
    44. Li, Zhiyong & Wan, Yifan & Wang, Tianyi & Yu, Mei, 2023. "Factor-timing in the Chinese factor zoo: The role of economic policy uncertainty," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    45. Marco Caiffa & Vincenzo Farina & Lucrezia Fattobene, 2021. "CEO Duality: Newspapers and Stock Market Reactions," JRFM, MDPI, vol. 14(1), pages 1-18, January.
    46. Wei Zhang & Yingxiu Zhao & Pengfei Wang & Dehua Shen, 2020. "Investor Sentiment and the Return Rate of P2P Lending Platform," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 97-113, March.
    47. Chao Liang & Yaojie Zhang & Xiafei Li & Feng Ma, 2022. "Which predictor is more predictive for Bitcoin volatility? And why?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1947-1961, April.
    48. Li, Fengyu & Yang, Mozhu & Zhang, Tong, 2023. "Does prospectus readability matter for bond issuance pricing? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    49. Lin, Hai & Tao, Xinyuan & Wu, Chunchi, 2022. "Forecasting earnings with combination of analyst forecasts," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 133-159.
    50. Haritha P H & Abdul Rishad, 2020. "An empirical examination of investor sentiment and stock market volatility: evidence from India," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-15, December.
    51. Jin, Zuben, 2024. "Business aspects in focus, investor underreaction and return predictability," Journal of Corporate Finance, Elsevier, vol. 84(C).
    52. Arikan, Mazhar & Kara, Mehmet & Masli, Adi & Xi, Yaoyi, 2023. "Political euphoria and corporate disclosures: An investigation of CEO partisan alignment with the president of the United States," Journal of Accounting and Economics, Elsevier, vol. 75(2).
    53. Manish Jha, 2024. "Do Activists Align with Larger Mutual Funds?," Papers 2411.16553, arXiv.org.
    54. John Berns & Patty Bick & Ryan Flugum & Reza Houston, 2022. "Do changes in MD&A section tone predict investment behavior?," The Financial Review, Eastern Finance Association, vol. 57(1), pages 129-153, February.
    55. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    56. Ma, Feng & Wu, Hanlin & Zeng, Qing, 2024. "Biodiversity and stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    57. Mengxi He & Yaojie Zhang & Yudong Wang & Danyan Wen, 2024. "Modelling and forecasting crude oil price volatility with climate policy uncertainty," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    58. Fuwei Jiang & Fujing Jin & Kejia Zhang, 2023. "Financial openness and profitability premium: Causal evidence from the Shanghai‐Hong Kong Stock Connect," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 451-483, March.
    59. Nan Hu & Xingnan Xue & Ling Liu, 2022. "The impact of air pollution on financial reporting quality: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(3), pages 3609-3644, September.
    60. Pablo Pastory y Camarasa & Martien Lamers, 2023. "Do Actions Follow Words? How bank sentiment predicts credit growth," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1073, Ghent University, Faculty of Economics and Business Administration.
    61. Onur Bayar & Emre Kesici, 2024. "The impact of social media on venture capital financing: evidence from Twitter interactions," Review of Quantitative Finance and Accounting, Springer, vol. 62(1), pages 195-224, January.
    62. Fernandez-Perez, Adrian & Garel, Alexandre & Indriawan, Ivan, 2020. "Music sentiment and stock returns," Economics Letters, Elsevier, vol. 192(C).
    63. Danso, Albert & Lartey, Theophilus & Amankwah-Amoah, Joseph & Adomako, Samuel & Lu, Qinye & Uddin, Moshfique, 2019. "Market sentiment and firm investment decision-making," International Review of Financial Analysis, Elsevier, vol. 66(C).
    64. Du, Rui & Mino, Ajkel & Wang, Jianghao & Zheng, Siqi, 2024. "Transboundary vegetation fire smoke and expressed sentiment: Evidence from Twitter," Journal of Environmental Economics and Management, Elsevier, vol. 124(C).
    65. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    66. Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    67. Yongan Xu & Chao Liang, 2024. "Does extreme climate concern drive equity premiums? Evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    68. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    69. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    70. Bryan T. Kelly & Asaf Manela & Alan Moreira, 2019. "Text Selection," NBER Working Papers 26517, National Bureau of Economic Research, Inc.
    71. Wu, Di & Gao, Shenghao & Chan, Kam C. & Cheng, Xiaoke, 2022. "Do firms strategically respond to retail investors on the online interactive information disclosure platform?," Finance Research Letters, Elsevier, vol. 47(PA).
    72. Xie, Yutang & Peng, Huan & Feng, Ting, 2024. "Pricing stock index futures with sentiments," Finance Research Letters, Elsevier, vol. 61(C).
    73. Haitham A. Al‐Zoubi & Jennifer A. O'Sullivan & Aktham I. Al‐Maghyereh & Brendan J. Lambe, 2023. "Disentangling Sentiment from Cyclicality in Firm Capital Structure," Abacus, Accounting Foundation, University of Sydney, vol. 59(2), pages 570-605, June.
    74. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    75. Padma Kadiyala, 2022. "Response of ETF flows and long-run returns to investor sentiment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(4), pages 489-531, December.
    76. Karavitis, Panagiotis & Kazakis, Pantelis, 2022. "Political sentiment and syndicated loan borrowing costs of multinational enterprises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    77. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    78. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
    79. Chen Gu & Xu Guo & Ruwan Adikaram & Kam C. Chan & Jing Lu, 2023. "Treasury return predictability and investor sentiment," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(4), pages 905-924, December.
    80. Ma, Tian & Leong, Wen Jun & Jiang, Fuwei, 2023. "A latent factor model for the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 87(C).
    81. Huang, Dashan & Jiang, Fuwei & Li, Kunpeng & Tong, Guoshi & Zhou, Guofu, 2023. "Are bond returns predictable with real-time macro data?," Journal of Econometrics, Elsevier, vol. 237(2).
    82. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    83. Alsheikh, Muna Ibrahim, 2020. "Beliefs-dependent utilities do influence firm-specific wealth (executives’ inside equity holdings)," Journal of Economics and Business, Elsevier, vol. 109(C).
    84. Tianlun Fei & Xiaoquan Liu & Conghua Wen, 2023. "Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1594-1621, November.
    85. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    86. Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
    87. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    88. Qiu, Rui & Liu, Jing & Li, Yan, 2023. "Long-term adjusted volatility: Powerful capability in forecasting stock market returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    89. Zongwu Cai & Pixiong Chen, 2024. "Online Investor Sentiment via Machine Learning," Mathematics, MDPI, vol. 12(20), pages 1-14, October.
    90. Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers 19116, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    91. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    92. Can Huang & Yuqiang Cao & Meiting Lu & Yaowen Shan & Yizhou Zhang, 2023. "Messages in online stock forums and stock price synchronicity: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3011-3041, September.
    93. Huang, Shuyang & Zeng, Ming, 2022. "Political sentiment and MAX effect," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    94. Zhifeng Dai & Jie Kang & Hua Yin, 2023. "Forecasting equity risk premium: A new method based on wavelet de‐noising," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4331-4352, October.
    95. Shuyu Zhang & Walter Aerts & Dunli Zhang & Zishan Chen, 2022. "Positive tone and initial coin offering," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(2), pages 2237-2266, June.
    96. Tian Ma & Cunfei Liao & Fuwei Jiang, 2023. "Timing the factor zoo via deep learning: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 485-505, March.
    97. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    98. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    99. Dai, Zhifeng & Zhu, Huan & Kang, Jie, 2021. "New technical indicators and stock returns predictability," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 127-142.
    100. Ren, Zhaoyue & Xiong, Yang & Huang, Yongjian, 2024. "Local officials’ sentiment and government financing cost: Evidence from Chengtou bonds in China," Finance Research Letters, Elsevier, vol. 63(C).
    101. Ruan, Xinfeng & Zhang, Jin E., 2019. "Moment spreads in the energy market," Energy Economics, Elsevier, vol. 81(C), pages 598-609.
    102. Tao, Ran & Brooks, Chris & Bell, Adrian R., 2020. "When is a MAX not the MAX? How news resolves information uncertainty," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 33-51.
    103. Wang, Cheng & Han, Jing, 2023. "Prospect theory and mutual fund flows: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    104. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    105. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
    106. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    107. Jiang, Yuexiang & Fu, Tao & Long, Huaigang & Zaremba, Adam & Zhou, Wenyu, 2022. "Real estate climate index and aggregate stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    108. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    109. Xiaobo Tang & Shixuan Li & Mingliang Tan & Wenxuan Shi, 2020. "Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 769-787, August.
    110. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    111. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
    112. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    113. Yue, Sishi & Yang, Mo & Dong, Dayong, 2024. "Do enterprises adopting digital finance exhibit higher values? Based on textual analysis," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    114. Luiz Renato Lima & Lucas Lúcio Godeiro, 2023. "Equity‐premium prediction: Attention is all you need," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 105-122, January.
    115. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    116. Song, Ziyu & Yu, Changrui, 2022. "Investor sentiment indices based on k-step PLS algorithm: A group of powerful predictors of stock market returns," International Review of Financial Analysis, Elsevier, vol. 83(C).
    117. Guglielmo Maria Caporale & Faek Menla Ali & Fabio Spagnolo & Nicola Spagnolo, 2020. "Cross-Border Portfolio Flows and News Media Coverage," CESifo Working Paper Series 8112, CESifo.
    118. Pham, Man Duy (Marty) & Nguyen, Thu Ha, 2024. "When a gift resembles a trojan horse: CEO stock gift and stock price crash risk," The British Accounting Review, Elsevier, vol. 56(4).
    119. Wenbo Ma & Xinjie Wang & Yuan Wang & Ge Wu, 2021. "Measuring misleading information in IPO prospectuses," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 819-843, October.
    120. Yetaotao Qiu & Michel Magnan & Shafu Zhang, 2023. "Competitive threat and strategic disclosure during the IPO quiet period," Review of Quantitative Finance and Accounting, Springer, vol. 60(1), pages 375-416, January.
    121. Zhang, Shengpeng & Li, Yaokuang & Liang, Ruixin & He, Yu, 2024. "Does management tone matter in information disclosure? Evidence from IPO online roadshows in the SSE STAR market," International Review of Financial Analysis, Elsevier, vol. 94(C).
    122. Rüdiger Weber & Annika Weber & Christine Laudenbach & Johannes Wohlfart, 2021. "Beliefs About the Stock Market and Investment Choices: Evidence from a Field Experiment," CEBI working paper series 21-17, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    123. Wen, Danyan & Wang, Huihui & Wang, Yudong & Xiao, Jihong, 2024. "Crude oil futures and the short-term price predictability of petroleum products," Energy, Elsevier, vol. 307(C).
    124. Yao Ge & Zheng Qiao & Zhe Shen & Zhiyu Zhang, 2023. "Production similarity and the cross‐section of stock returns: A machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 4849-4882, December.
    125. Tri Minh Phan, 2024. "Sentiment-semantic word vectors: A new method to estimate management sentiment," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-22, December.
    126. Ung, Sze Nie & Gebka, Bartosz & Anderson, Robert D.J., 2023. "Is sentiment the solution to the risk–return puzzle? A (cautionary) note," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    127. Roland Füss & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia In The Cross-Section of Global Equity," Working Papers on Finance 1913, University of St. Gallen, School of Finance, revised May 2020.
    128. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
    129. Andrew Todd & James Bowden & Yashar Moshfeghi, 2024. "Text‐based sentiment analysis in finance: Synthesising the existing literature and exploring future directions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(1), March.
    130. Tran, Vu Le, 2023. "Sentiment and covariance characteristics," International Review of Financial Analysis, Elsevier, vol. 86(C).
    131. Meng, Bo & Vijh, Anand M., 2021. "Stock merger activity and industry performance," Journal of Banking & Finance, Elsevier, vol. 129(C).
    132. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    133. Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.
    134. Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023. "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 860-872.
    135. Yong Ma & Lu Yan & Dongtao Pan, 2024. "The power of news data in forecasting tail risk: evidence from China," Empirical Economics, Springer, vol. 67(6), pages 2607-2642, December.
    136. Guo, Haifeng & Wang, Ying & Wang, Bo & Ge, Yuanjing, 2022. "Does prospectus AE affect IPO underpricing? A content analysis of the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 1-12.
    137. Lu, Fei & Ma, Feng & Hu, Shiyang, 2024. "Does energy consumption play a key role? Re-evaluating the energy consumption-economic growth nexus from GDP growth rates forecasting," Energy Economics, Elsevier, vol. 129(C).
    138. Li, Hui & Zeng, Min & Liu, Ya-Fei, 2023. "Secret sentiments make for good announcements: Does unjustified managerial belief benefit tourism firm performance?," Annals of Tourism Research, Elsevier, vol. 103(C).
    139. Weiguo Zhang & Xue Gong & Chao Wang & Xin Ye, 2021. "Predicting stock market volatility based on textual sentiment: A nonlinear analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1479-1500, December.
    140. Zhang, Yi & Hu, Ailing & Wang, Jiahua & Zhang, Yaojie, 2022. "Detection of fraud statement based on word vector: Evidence from financial companies in China," Finance Research Letters, Elsevier, vol. 46(PB).
    141. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    142. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    143. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    144. Lu, Jing & Chen, Rongze, 2023. "Do individual investors pay attention to the information acquisition activities of institutional investors?," Finance Research Letters, Elsevier, vol. 58(PD).
    145. Li, Guowen & Wang, Shuai & Feng, Yuyao, 2024. "Making differences work: Financial fraud detection based on multi-subject perceptions," Emerging Markets Review, Elsevier, vol. 60(C).
    146. Gregory, Richard Paul, 2021. "What determines Manager and Investor Sentiment?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    147. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    148. An, Suwei, 2023. "Essays on incentive contracts, M&As, and firm risk," Other publications TiSEM dd97d2f5-1c9d-47c5-ba62-f, Tilburg University, School of Economics and Management.
    149. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    150. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    151. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    152. Hitoshi Iwasaki & Ying Chen & Jun Tu, 2023. "Topic tones of analyst reports and stock returns: A deep learning approach," International Review of Finance, International Review of Finance Ltd., vol. 23(4), pages 831-858, December.
    153. Xiao Wu, Dong & Yao, Xiao & Luan Guo, Jian, 2021. "Is Textual Tone Informative or Inflated for Firm’s Future Value? Evidence from Chinese Listed Firms," Economic Modelling, Elsevier, vol. 94(C), pages 513-525.
    154. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    155. Makridis, Christos A. & Schloetzer, Jason D., 2023. "Extreme local temperatures lower expressed sentiment about U.S. economic conditions with implications for the stock returns of local firms," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    156. Zhou, Xuemei & Liu, Qiang & Guo, Shuxin, 2021. "Do overnight returns explain firm-specific investor sentiment in China?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 451-477.
    157. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    158. Wasim ul Rehman & Omur Saltik & Faryal Jalil & Suleyman Degirmen, 2024. "Viral decisions: unmasking the impact of COVID-19 info and behavioral quirks on investment choices," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
    159. Meng‐Feng Yen & Yu‐Pei Huang & Liang‐Chih Yu & Yueh‐Ling Chen, 2022. "A Two-Dimensional Sentiment Analysis of Online Public Opinion and Future Financial Performance of Publicly Listed Companies," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1677-1698, April.
    160. Rei Yamamoto & Naoya Kawadai & Masataka Kurita & Satoshi Baba, 2022. "Managements’ tone strategies by earnings call transcripts in the global markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(3), pages 246-255, May.
    161. Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie & Wang, Qunwei, 2024. "Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors," Energy Economics, Elsevier, vol. 133(C).
    162. Liu, Yi & Jin, Justin & Zhang, Zehua & Zhao, Ran, 2022. "Firm-level political sentiment and corporate tax avoidance," International Review of Financial Analysis, Elsevier, vol. 84(C).
    163. Brückbauer, Frank & Cezanne, Thibault, 2022. "Bank manager sentiment, loan growth and bank risk," ZEW Discussion Papers 22-066, ZEW - Leibniz Centre for European Economic Research.
    164. Adnan Abo Al Haija & Rahma Lahyani, 2023. "Dynamic interactions of actual stock returns with forecasted stock returns and investors’ risk aversion: empirical evidence interplaying the impact of Covid-19 pandemic," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 1129-1149, October.
    165. Dang, Man & Puwanenthiren, Premkanth & Nguyen, Manh Toan & Hoang, Viet Anh & Mazur, Mieszko & Henry, Darren, 2022. "Does managerial tone matter for stock liquidity? Evidence from textual disclosures," Finance Research Letters, Elsevier, vol. 48(C).
    166. Gianni La Cava, 2021. "Smells Like Animal Spirits: The Effect of Corporate Sentiment on Investment," RBA Research Discussion Papers rdp2021-11, Reserve Bank of Australia.
    167. Zaremba, Adam & Szyszka, Adam & Long, Huaigang & Zawadka, Dariusz, 2020. "Business sentiment and the cross-section of global equity returns," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    168. Shrestha, Keshab & Naysary, Babak, 2023. "ESG and economic policy uncertainty: A wavelet application," Finance Research Letters, Elsevier, vol. 58(PD).
    169. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    170. Cai, Haidong & Jiang, Ying & Liu, Xiaoquan, 2022. "Investor attention, aggregate limit-hits, and stock returns," International Review of Financial Analysis, Elsevier, vol. 83(C).
    171. Li, Xiaowei & Wu, Zhengyu & Zhang, Hao & Zhang, Lu, 2024. "Risk-neutral skewness and stock market returns: A time-series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    172. Wang, Chunlan & Xin, Jianxuan & Sun, Fangfang & Shi, Yan & Du, Yuxuan, 2024. "The effects of manager sentiment in financial disclosure: Perspectives of operational efficiency and market reaction," Finance Research Letters, Elsevier, vol. 64(C).
    173. Jędrzej Białkowski & Moritz Wagner & Xiaopeng Wei, 2023. "Differences between NZ and U.S. individual investor sentiment: More noise or more information?," Working Papers in Economics 23/11, University of Canterbury, Department of Economics and Finance.
    174. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    175. Ding, Rui & Guo, Jintong & Zhang, Min, 2024. "Practice a poker face: Manager emotion and investor sentiment," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    176. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    177. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    178. Hasan, Md. Tanvir, 2022. "The sum of all SCARES COVID-19 sentiment and asset return," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 332-346.
    179. Zongwu Cai & Pixiong Chen, 2022. "New Online Investor Sentiment and Asset Returns," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202216, University of Kansas, Department of Economics, revised Nov 2022.
    180. Fang, Yue & Luo, Deming & Yao, Zhongwei, 2024. "Belief dispersion in the Chinese stock market and fund flows," Journal of Banking & Finance, Elsevier, vol. 166(C).
    181. Szymon Lis, 2024. "Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence," Papers 2411.13180, arXiv.org.
    182. Guohao Tang & Fuwei Jiang & Xinlin Qi & Nan Huang, 2021. "It takes two to tango: Fundamental timing in stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5259-5277, October.
    183. Christine Laudenbach & Annika Weber & Johannes Wohlfart, 2021. "Beliefs About the Stock Market and Investment Choices: Evidence from a Field Experiment," ECONtribute Discussion Papers Series 128, University of Bonn and University of Cologne, Germany.
    184. Lee, Geul & Ryu, Doojin, 2024. "Investor sentiment or information content? A simple test for investor sentiment proxies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).

  6. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.

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    2. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    3. Khan, Mostafa Saidur Rahim & Kato, Hideaki Kiyoshi & Bremer, Marc, 2019. "Short sales constraints and stock returns: How do the regulations fare?," Journal of the Japanese and International Economies, Elsevier, vol. 54(C).
    4. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    5. Vikas Agarwal & Stefan Ruenzi & Florian Weigert, 2018. "Unobserved Performance of Hedge Funds," Working Papers on Finance 1825, University of St. Gallen, School of Finance.
    6. Fernando Chague & Rodrigo De Losso, Bruno Giovannetti, 2017. "Uncovering Skilled Short-sellers," Working Papers, Department of Economics 2017_01, University of São Paulo (FEA-USP).
    7. Esther Eiling & Raymond Kan & Ali Sharifkhani, 2018. "Sectoral Labor Reallocation and Return Predictability," Working Papers 2018-006, Human Capital and Economic Opportunity Working Group.
    8. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    9. Larry Su & Elmina Homapour & Francisco Chiclana, 2022. "Short-Sale Constraints and Stock Prices: Evidence from Implementation of Securities Refinancing Mechanism in Chinese Stock Markets," Mathematics, MDPI, vol. 10(17), pages 1-21, September.
    10. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    11. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    12. Kostakis, Alexandros & Magdalinos, Tassos & Stamatogiannis, Michalis P., 2023. "Taking stock of long-horizon predictability tests: Are factor returns predictable?," Journal of Econometrics, Elsevier, vol. 237(2).
    13. Wei Guo & Xinfeng Ruan & Sebastian A. Gehricke & Jin E. Zhang, 2023. "Term spreads of implied volatility smirk and variance risk premium," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(7), pages 829-857, July.
    14. Yaojie Zhang & Qingxiang Han & Mengxi He, 2024. "Forecasting stock market returns with a lottery index: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1595-1606, August.
    15. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    16. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    17. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    18. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    19. Chague, Fernando & De-Losso, Rodrigo & Giovannetti, Bruno, 2019. "The short-selling skill of institutions and individuals," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 77-91.
    20. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Business School, revised Feb 2018.
    21. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    22. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Role of hedging on crypto returns predictability: A new habit-based explanation," Finance Research Letters, Elsevier, vol. 55(PB).
    23. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    24. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    25. Pedro A.C. Saffi & Carles Vergara‐Alert, 2020. "The Big Short: Short Selling Activity and Predictability in House Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(4), pages 1030-1073, December.
    26. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    27. Bao, Jack & Hou, Kewei & Zhang, Shaojun A., 2016. "Systemic Default and Return Predictability in the Stock and Bond Markets," Working Paper Series 2016-2, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    28. Mihai, Marius M. & Mansur, Iqbal, 2022. "Forecasting crash risk in U.S. bank returns—The role of credit booms," Journal of Corporate Finance, Elsevier, vol. 76(C).
    29. Antonio Gargano & Juan Sotes-Paladino & Patrick Verwijmeren, 2022. "Out of Sync: Dispersed Short Selling and the Correction of Mispricing," Working Papers 108, Red Nacional de Investigadores en Economía (RedNIE).
    30. Fabio Cereda & Fernando Chague & Rodrigo De Losso & Alan De Genaro & Bruno Giovannetti, 2020. "Price Transparency in OTC Equity Lending Markets: Evidence from a Loan Fee Benchmark," Working Papers, Department of Economics 2020_22, University of São Paulo (FEA-USP).
    31. Hadhri, Sinda & Ftiti, Zied, 2019. "Asset allocation and investment opportunities in emerging stock markets: Evidence from return asymmetry-based analysis," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 187-200.
    32. Xufeng Liu & Die Wan, 2022. "Does short‐selling affect mutual fund shareholdings? Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1887-1923, April.
    33. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    34. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    35. Baig, Ahmed S. & Blau, Benjamin M. & Butt, Hassan A. & Yasin, Awaid, 2022. "Do retail traders destabilize financial markets? An investigation surrounding the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 144(C).
    36. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    37. David Haab & Thomas Nitschka, 2017. "Predicting returns on asset markets of a small, open economy and the influence of global risks," Working Papers 2017-14, Swiss National Bank.
    38. Zhikai Zhang & Yaojie Zhang & Yudong Wang & Qunwei Wang, 2024. "The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 557-584, April.
    39. Fos, Vyacheslav & Appel, Ian & Bulka, Jordan, 2019. "Active Short Selling by Hedge Funds," CEPR Discussion Papers 13788, C.E.P.R. Discussion Papers.
    40. Afsin Sahin, 2019. "Loom of Symmetric Pass-Through," Economies, MDPI, vol. 7(1), pages 1-25, February.
    41. Dunbar, Kwamie, 2023. "CBDC uncertainty: Financial market implications," International Review of Financial Analysis, Elsevier, vol. 87(C).
    42. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    43. Antonio Gargano & Juan Sotes-Paladino & Patrick Verwijmeren, 2022. "Short of Capital: Stock Market Implications of Short Sellers’ Losses," Working Papers 116, Red Nacional de Investigadores en Economía (RedNIE).
    44. Li, Jun & Wang, Huijun & Yu, Jianfeng, 2018. "Aggregate Expected Investment Growth and Stock Market Returns," ADBI Working Papers 808, Asian Development Bank Institute.
    45. Chung, Chune Young & Liu, Chang & Wang, Kainan, 2021. "The big picture: The industry effect of short interest," International Review of Financial Analysis, Elsevier, vol. 76(C).
    46. Greppmair, Stefan & Jank, Stephan & Saffi, Pedro A. C. & Sturgess, Jason, 2024. "Securities lending and information acquisition," Discussion Papers 08/2024, Deutsche Bundesbank.
    47. José Afonso Faias & Juan Arismendi Zambrano, 2022. "Equity Risk Premium Predictability from Cross-Sectoral Downturns [International asset allocation with regime shifts]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 808-842.
    48. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," Working Papers hal-04141877, HAL.
    49. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    50. Atanasov, Victoria, 2021. "Unemployment and aggregate stock returns," Journal of Banking & Finance, Elsevier, vol. 129(C).
    51. Angelidis, Timotheos & Michairinas, Athanasios & Sakkas, Athanasios, 2024. "World ESG performance and economic activity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 93(C).
    52. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    53. Viet Anh Nguyen & Fan Zhang & Shanshan Wang & Jose Blanchet & Erick Delage & Yinyu Ye, 2021. "Robustifying Conditional Portfolio Decisions via Optimal Transport," Papers 2103.16451, arXiv.org, revised Apr 2024.
    54. Hanauer, Matthias X. & Lesnevski, Pavel & Smajlbegovic, Esad, 2023. "Surprise in short interest," Journal of Financial Markets, Elsevier, vol. 65(C).
    55. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    56. Guo, Xu & Wu, Chunchi, 2019. "Short interest, stock returns and credit ratings," Journal of Banking & Finance, Elsevier, vol. 108(C).
    57. Pyun, Sungjune, 2019. "Variance risk in aggregate stock returns and time-varying return predictability," Journal of Financial Economics, Elsevier, vol. 132(1), pages 150-174.
    58. Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
    59. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    60. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," EconomiX Working Papers 2019-8, University of Paris Nanterre, EconomiX.
    61. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    62. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    63. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    64. Jianlei Han & Martina Linnenluecke & Zhangxin Liu & Zheyao Pan & Tom Smith, 2019. "A general equilibrium approach to pricing volatility risk," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
    65. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
    66. Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Predictive Power of Industrial Electricity Usage Revisited: Evidence from Nonparametric Causality Tests," Working Papers 201679, University of Pretoria, Department of Economics.
    67. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
    68. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    69. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    70. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    71. Greppmair, Stefan & Jank, Stephan & Smajlbegovic, Esad, 2023. "On the importance of fiscal space: Evidence from short sellers during the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 147(C).
    72. Yanbo Liu & Peter C.B. Phillips, 2021. "Robust Inference with Stochastic Local Unit Root Regressors in Predictive Regressions," Cowles Foundation Discussion Papers 2305, Cowles Foundation for Research in Economics, Yale University.
    73. Massimo Guidolin & Erwin Hansen & Gabriel Cabrera, 2023. "Time-Varying Risk Aversion and International Stock Returns," BAFFI CAREFIN Working Papers 23203, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    74. Di Maggio, Marco & Franzoni, Francesco & Massa, Massimo & Tubaldi, Roberto, 2024. "Strategic trading as a response to short sellers," Journal of Financial Markets, Elsevier, vol. 69(C).
    75. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    76. Ang (Chewie), Tze Chuan & Hayat, Aziz & Li, Bob, 2020. "Short-selling risk in Australia," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    77. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    78. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    79. Lin, Qi & Lin, Xi, 2021. "Are the profitability and investment factors valid ICAPM risk factors? Pre-1963 evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    80. Chague, Fernando Daniel & Bueno, Rodrigo de Losso da Silveira & Giovannetti, Bruno Cara, 2018. "The short-selling skill of institutions and individuals: a market-wide and out-of-sample analysis," Textos para discussão 469, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    81. Scott Cederburg & Travis L Johnson & Michael S O’Doherty, 2023. "On the Economic Significance of Stock Return Predictability," Review of Finance, European Finance Association, vol. 27(2), pages 619-657.
    82. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    83. Zhang, Wei & Wang, Pengfei & Li, Yi, 2021. "Bond intraday momentum," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    84. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    85. Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
    86. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    87. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    88. Hongwei Zhang & Qiang He & Ben Jacobsen & Fuwei Jiang, 2020. "Forecasting stock returns with model uncertainty and parameter instability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 629-644, August.
    89. Libo Yin & Jing Nie & Liyan Han, 2021. "Intermediary capital risk and commodity futures volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 577-640, May.
    90. Ólan Henry & Semih Kerestecioglu & Sam Pybis, 2024. "Can financial uncertainty forecast aggregate stock market returns?," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 33(2), pages 91-111, May.
    91. Zhifeng Dai & Jie Kang & Hua Yin, 2023. "Forecasting equity risk premium: A new method based on wavelet de‐noising," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4331-4352, October.
    92. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    93. Riza Demirer & Guilherme Demos & Rangan Gupta & Didier Sornette, 2017. "On the Predictability of Stock Market Bubbles: Evidence from LPPLS ConfidenceTM Multi-scale Indicators," Working Papers 201752, University of Pretoria, Department of Economics.
    94. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    95. Yongsheng Yi & Feng Ma & Dengshi Huang & Yaojie Zhang, 2019. "Interest rate level and stock return predictability," Review of Financial Economics, John Wiley & Sons, vol. 37(4), pages 506-522, October.
    96. Ben Chamberlain & Zhangxin (Frank) Liu & Lee A. Smales, 2023. "Short interest and the stock market relation with news sentiment from traditional and social media sources," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 321-334, June.
    97. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    98. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    99. Dai, Zhifeng & Zhu, Huan & Kang, Jie, 2021. "New technical indicators and stock returns predictability," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 127-142.
    100. Ruan, Xinfeng & Zhang, Jin E., 2019. "Moment spreads in the energy market," Energy Economics, Elsevier, vol. 81(C), pages 598-609.
    101. Jia, Xiaolan & Ruan, Xinfeng & Zhang, Jin E., 2023. "Carr and Wu’s (2020) framework in the oil ETF option market," Journal of Commodity Markets, Elsevier, vol. 31(C).
    102. Dai, Zhifeng & Zhang, Xiaotong & Liang, Chao, 2024. "Efficient predictability of oil price: The role of VIX-based panic index shadow line difference," Energy Economics, Elsevier, vol. 129(C).
    103. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    104. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
    105. Yan, Cheng & Wang, Xichen, 2018. "The non-persistent relationship between foreign equity flows and emerging stock market returns across quantiles," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 38-54.
    106. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    107. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
    108. Jiang, Yuexiang & Fu, Tao & Long, Huaigang & Zaremba, Adam & Zhou, Wenyu, 2022. "Real estate climate index and aggregate stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    109. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    110. Chen Gu & Xu Guo & Alexander Kurov & Raluca Stan, 2022. "The information content of the volatility index options trading volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(9), pages 1721-1737, September.
    111. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    112. Xu, Ke-Li, 2021. "On the serial correlation in multi-horizon predictive quantile regression," Economics Letters, Elsevier, vol. 200(C).
    113. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
    114. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    115. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    116. Gungor, Sermin & Luger, Richard, 2020. "Small-sample tests for stock return predictability with possibly non-stationary regressors and GARCH-type effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 750-770.
    117. Duong, Huu Nhan & Kalev, Petko S. & Tian, Xiao, 2023. "Short selling, divergence of opinion and volatility in the corporate bond market," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    118. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    119. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    120. Qiao, Fang & Xu, Lai & Zhang, Xiaoyan & Zhou, Hao, 2024. "Variance risk premiums in emerging markets," Journal of Banking & Finance, Elsevier, vol. 167(C).
    121. Baig, Ahmed S. & Blau, Benjamin M. & Butt, Hassan A. & Yasin, Awaid, 2023. "Reprint of: Do retail traders destabilize financial markets? An investigation surrounding the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 147(C).
    122. Dunbar, Kwamie & Jiang, Jing, 2020. "What do movements in financial traders’ net long positions reveal about aggregate stock returns?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    123. Biao Guo & Qian Han & Hai Lin, 2018. "Are there gains from using information over the surface of implied volatilities?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 645-672, June.
    124. Chen, Qiang & Han, Yu, 2023. "Options market ambiguity and its information content," Journal of Financial Markets, Elsevier, vol. 64(C).
    125. Wang, Yuchen & Wang, Xiaoming, 2023. "Economic policy uncertainty and information intermediary: The case of short seller," Economic Modelling, Elsevier, vol. 120(C).
    126. Wen, Danyan & Wang, Huihui & Wang, Yudong & Xiao, Jihong, 2024. "Crude oil futures and the short-term price predictability of petroleum products," Energy, Elsevier, vol. 307(C).
    127. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    128. Kai‐Jiun Chang & Mao‐Wei Hung & Yaw‐Huei Wang & Kuang‐Chieh Yen, 2019. "Volatility information implied in the term structure of VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 56-71, January.
    129. Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018. "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, vol. 70(C), pages 472-483.
    130. Zhu, Zhaobo & Duan, Xinrui & Sun, Licheng & Tu, Jun, 2019. "Momentum and reversal: The role of short selling," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 95-110.
    131. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    132. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    133. Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
    134. Cashman, George D. & Harrison, David M. & Sheng, Hainan, 2022. "Short sales, short risk, and return predictability in Asia-Pacific real estate markets," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    135. Imran Yousaf & Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2022. "Hedge and Safe Haven Properties of Gold, US Treasury, Bitcoin, and Dollar/CHF against the FAANA Companies and S&P 500," Working Papers 202227, University of Pretoria, Department of Economics.
    136. Chen, Zhuo & Li, Pengfei & Wang, Zhengwei & Zhang, Bohui, 2024. "Leveraged trading and stock returns: Evidence from international stock markets," Journal of Financial Markets, Elsevier, vol. 69(C).
    137. Brennan, M.J. & Taylor, Alex P., 2023. "Expected returns and risk in the stock market," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 276-300.
    138. Sakariyahu, Rilwan & Lawal, Rodiat & Adigun, Rasheed & Paterson, Audrey & Johan, Sofia, 2024. "One crash, too many: Global uncertainty, sentiment factors and cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 94(C).
    139. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    140. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    141. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    142. Victoria Atanasov & Stig V. Møller & Richard Priestley, 2020. "Consumption Fluctuations and Expected Returns," Journal of Finance, American Finance Association, vol. 75(3), pages 1677-1713, June.
    143. Xianfeng Hao & Yudong Wang, 2023. "Cloud cover and expected oil returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    144. Zhang, Wei & Wang, Pengfei & Li, Yi, 2020. "Intraday momentum in Chinese commodity futures markets," Research in International Business and Finance, Elsevier, vol. 54(C).
    145. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    146. Fabian Hollstein & Marcel Prokopczuk, 2023. "Managing the Market Portfolio," Management Science, INFORMS, vol. 69(6), pages 3675-3696, June.
    147. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    148. Marshall, Ben R. & Nguyen, Hung T. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2021. "Country governance and international equity returns," Journal of Banking & Finance, Elsevier, vol. 122(C).
    149. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    150. Li, Jun & Wang, Huijun & Yu, Jianfeng, 2021. "Aggregate expected investment growth and stock market returns," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 618-638.
    151. Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
    152. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    153. Yousaf, Imran & Plakandaras, Vasilios & Bouri, Elie & Gupta, Rangan, 2023. "Hedge and safe-haven properties of FAANA against gold, US Treasury, bitcoin, and US Dollar/CHF during the pandemic period," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    154. Arseny Gorbenko & Marcin Kacperczyk, 2023. "Short Interest and Aggregate Stock Returns: International Evidence," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(4), pages 691-733.
    155. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    156. Achilles, Catrina & Limbach, Peter & Wolff, Michael & Yoon, Aaron, 2024. "Inside the blackbox of firm environmental efforts: Evidence from emissions reduction initiatives," CFR Working Papers 24-05, University of Cologne, Centre for Financial Research (CFR).
    157. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    158. Eliezer Fich & Viktoriya Lantushenko & Clemens Sialm, 2019. "Institutional Trading Around M&A Announcements," NBER Working Papers 25814, National Bureau of Economic Research, Inc.
    159. Jungah Yoon & Xinfeng Ruan & Jin E. Zhang, 2022. "VIX option‐implied volatility slope and VIX futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1002-1038, June.
    160. Xiaolan Jia & Xinfeng Ruan & Jin E. Zhang, 2021. "The implied volatility smirk of commodity options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 72-104, January.
    161. Gorovyy, Sergiy & Kelly, Patrick J. & Kuzmina, Olga, 2021. "Does secrecy signal skill? Own-investor secrecy and hedge fund performance," Journal of Banking & Finance, Elsevier, vol. 133(C).
    162. Yuan Liao & Xinjie Ma & Andreas Neuhierl & Zhentao Shi, 2023. "Economic Forecasts Using Many Noises," Papers 2312.05593, arXiv.org, revised Dec 2023.
    163. David R. Haab & Thomas Nitschka, 2019. "What Goliaths and Davids among Swiss firms tell us about expected returns on Swiss asset markets," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 155(1), pages 1-17, December.
    164. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    165. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    166. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    167. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    168. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
    169. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    170. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2023. "The effect of uncertainty on stock market volatility and correlation," Journal of Banking & Finance, Elsevier, vol. 154(C).
    171. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    172. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    173. Vasilios Plakandaras & Ioannis Pragidis & Paris Karypidis, 2024. "Deciphering the U.S. metropolitan house price dynamics," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 52(2), pages 434-485, March.
    174. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    175. Cao, Charles & Simin, Timothy & Xiao, Han, 2020. "Predicting the equity premium with the implied volatility spread," Journal of Financial Markets, Elsevier, vol. 51(C).
    176. Guettler, Andre & Hable, Patrick & Launhardt, Patrick & Miebs, Felix, 2023. "Aggregate insider trading in the S&P 500 and the predictability of international equity premia," Finance Research Letters, Elsevier, vol. 54(C).
    177. Cao, Charles & Simin, Timothy & Xiao, Han, 2019. "Predicting the equity premium with the implied volatility spread," MPRA Paper 103651, University Library of Munich, Germany.
    178. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    179. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    180. Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie & Wang, Qunwei, 2024. "Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors," Energy Economics, Elsevier, vol. 133(C).
    181. Pan, Zheyao & Chan, Kam Fong, 2018. "A new government bond volatility index predictor for the U.S. equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 200-215.
    182. Pan, Zhiyuan & Huang, Xiao & Liu, Li & Huang, Juan, 2023. "Geopolitical uncertainty and crude oil volatility: Evidence from oil-importing and oil-exporting countries," Finance Research Letters, Elsevier, vol. 52(C).
    183. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    184. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    185. Chiang, I-Hsuan Ethan & Hughen, W. Keener, 2017. "Do oil futures prices predict stock returns?," Journal of Banking & Finance, Elsevier, vol. 79(C), pages 129-141.
    186. Huynh, Nhan, 2023. "Unemployment beta and the cross-section of stock returns: Evidence from Australia," International Review of Financial Analysis, Elsevier, vol. 86(C).
    187. Dong, Yunhe & Luo, Haoyi & Xu, Zijin & Yang, Xing, 2024. "Investing while lending: Do index funds improve managerial information disclosure?," International Review of Financial Analysis, Elsevier, vol. 94(C).
    188. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    189. Ye Li & Chen Wang, 2023. "Valuation Duration of the Stock Market," Papers 2310.07110, arXiv.org.
    190. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    191. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou, 2021. "Gold Against the Machine," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 5-28, January.
    192. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    193. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    194. Johan Maharjan & Seung Won Lee, 2022. "Short‐selling pressure and year‐over‐year MD&A modifications," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(3), pages 3513-3562, September.
    195. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    196. Bing Han & Gang Li, 2021. "Information Content of Aggregate Implied Volatility Spread," Management Science, INFORMS, vol. 67(2), pages 1249-1269, February.
    197. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.
    198. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
    199. Chen Gu & Denghui Chen & Raluca Stan, 2021. "Investor sentiment and the market reaction to macroeconomic news," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1412-1426, September.
    200. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.

  7. Bai, Jushan & Zhou, Guofu, 2015. "Fama–MacBeth two-pass regressions: Improving risk premia estimates," Finance Research Letters, Elsevier, vol. 15(C), pages 31-40.

    Cited by:

    1. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    2. Cavalcante-Filho, Elias & Chague, Fernando & De-Losso, Rodrigo & Giovannetti, Bruno, 2022. "US risk premia under emerging markets constraints," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 217-230.
    3. José Luis Montiel Olea & Pietro Ortoleva & Mallesh Pai & Andrea Prat, 2021. "Competing Models," Working Papers 2021-89, Princeton University. Economics Department..
    4. M. Hashem Pesaran & Ron P. Smith, 2021. "Arbitrage Pricing Theory, the Stochastic Discount Factor and Estimation of Risk Premia from Portfolios," CESifo Working Paper Series 9001, CESifo.
    5. M. Hashem Pesaran & Ron P. Smith, 2019. "The Role of Factor Strength and Pricing Errors for Estimation and Inference in Asset Pricing Models," CESifo Working Paper Series 7919, CESifo.
    6. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    7. M. Hashem Pesaran & Run Smith, 2021. "Arbitrage pricing theory, the stochastic discount factor and estimation of risk premia in portfolios," BCAM Working Papers 2108, Birkbeck Centre for Applied Macroeconomics.
    8. M. Hashem Pesaran & Ron P. Smith, 2021. "Factor Strengths, Pricing Errors, and Estimation of Risk Premia," CESifo Working Paper Series 8947, CESifo.

  8. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.

    Cited by:

    1. Zuzana Rakovska & Dominika Ehrenbergerova & Martin Hodula, 2020. "The Power of Sentiment: Irrational Beliefs of Households and Consumer Loan Dynamics," Working Papers 2020/10, Czech National Bank.
    2. Li, Yuan & Ran, Jimmy, 2020. "Investor Sentiment and Stock Price Premium Validation with Siamese Twins from China," Journal of Multinational Financial Management, Elsevier, vol. 57.
    3. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    4. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    5. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    6. Yong Jiang & Zhongbao Zhou, 2018. "Does the time horizon of the return predictive effect of investor sentiment vary with stock characteristics? A Granger causality analysis in the frequency domain," Papers 1803.02962, arXiv.org.
    7. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    8. Chen, Rongda & Wu, Ling & Jin, Chenglu & Wang, Shengnan, 2021. "Unintended investor sentiment on bank financial products: Evidence from China," Emerging Markets Review, Elsevier, vol. 49(C).
    9. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    10. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2023. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 126151, London School of Economics and Political Science, LSE Library.
    11. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    12. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    13. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    14. Wang, Yubao & Huang, Xiaozhou & Huang, Zhendong, 2024. "Energy-related uncertainty and Chinese stock market returns," Finance Research Letters, Elsevier, vol. 62(PB).
    15. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    16. Jian Chen & Fuwei Jiang & Guoshi Tong, 2017. "Economic policy uncertainty in China and stock market expected returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1265-1286, December.
    17. Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022. "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    18. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
    19. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    20. Yun Liu & Dengshi Huang & Jianan Zhou & Sirui Wang, 2024. "Does image sentiment of major public emergency affect the stock market performance? New insight from deep learning techniques," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 4447-4472, December.
    21. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    22. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    23. Cui, Yueting & Gavriilidis, Konstantinos & Gebka, Bartosz & Kallinterakis, Vasileios, 2024. "Numerological superstitions and market-wide herding: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 93(C).
    24. Zhang, Lixia & Luo, Qin & Guo, Xiaozhu & Umar, Muhammad, 2022. "Medium-term and long-term volatility forecasts for EUA futures with country-specific economic policy uncertainty indices," Resources Policy, Elsevier, vol. 77(C).
    25. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
    26. Chue, Timothy K. & Gul, Ferdinand A. & Mian, G. Mujtaba, 2019. "Aggregate investor sentiment and stock return synchronicity," Journal of Banking & Finance, Elsevier, vol. 108(C).
    27. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    28. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    29. Riso, Luigi & Vacca, Gianmarco, 2024. "Sentiment dynamics and volatility: A study based on GARCH-MIDAS and machine learning," Finance Research Letters, Elsevier, vol. 62(PB).
    30. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    31. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    32. Yaojie Zhang & Qingxiang Han & Mengxi He, 2024. "Forecasting stock market returns with a lottery index: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1595-1606, August.
    33. ALAJEKWU, Udoka Bernard & OBIALOR, Michael Chukwumee & OKORO, Cyprian Okey, 2017. "Ffect Of Investor Sentiment On Future Returns In The Nigerian Stock Market," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 17(2), pages 103-126.
    34. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    35. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021. "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers 202118, University of Pretoria, Department of Economics.
    36. Chen, Rongda & Yu, Jingjing & Jin, Chenglu & Bao, Weiwei, 2019. "Internet finance investor sentiment and return comovement," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 151-161.
    37. Rui Liu & Jiayou Liang & Haolong Chen & Yujia Hu, 2024. "Analyst Reports and Stock Performance: Evidence from the Chinese Market," Papers 2411.08726, arXiv.org.
    38. Jin, Xuejun & Chen, Cheng & Yang, Xiaolan, 2024. "The effect of international media news on the global stock market," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 50-69.
    39. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    40. Guo, Xu & Gu, Chen & Zhang, Chengping & Li, Shenru, 2024. "Institutional herding and investor sentiment," Journal of Financial Markets, Elsevier, vol. 68(C).
    41. Shi, Qi & Li, Bin, 2022. "Further evidence on financial information and economic activity forecasts in the United States," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    42. Liu, Hong & Tang, Xiaoxiao & Zhou, Guofu, 2022. "Recovering the FOMC risk premium," Journal of Financial Economics, Elsevier, vol. 145(1), pages 45-68.
    43. Xu, Yongan & Liang, Chao & Wang, Jianqiong, 2023. "Financial stress and returns predictability: Fresh evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    44. Liu, Zhenhua & Chen, Shumin & Zhong, Hongyu & Ding, Zhihua, 2024. "Coal price shocks, investor sentiment, and stock market returns," Energy Economics, Elsevier, vol. 135(C).
    45. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    46. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    47. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Business School, revised Feb 2018.
    48. Zhang, Hang & Tsai, Wei-Che & Weng, Pei-Shih & Tsai, Pin-Chieh, 2023. "Overnight returns and investor sentiment: Further evidence from the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    49. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    50. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    51. Li, Tong & Chen, Hui & Liu, Wei & Yu, Guang & Yu, Yongtian, 2023. "Understanding the role of social media sentiment in identifying irrational herding behavior in the stock market," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 163-179.
    52. Yuan Li, 2022. "Mood Beta, Sentiment and Stock Returns in China," SAGE Open, , vol. 12(1), pages 21582440221, February.
    53. Shen, Shulin & Xia, Le & Shuai, Yulin & Gao, Da, 2022. "Measuring news media sentiment using big data for Chinese stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    54. Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
    55. Liao, Cunfei & Luo, Qianlin & Tang, Guohao, 2021. "Aggregate liquidity premium and cross-sectional returns: Evidence from China," Economic Modelling, Elsevier, vol. 104(C).
    56. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    57. Demirer, Riza & Yuksel, Asli & Yuksel, Aydin, 2022. "Time-varying risk aversion and currency excess returns," Research in International Business and Finance, Elsevier, vol. 59(C).
    58. Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," CEMA Working Papers 678, China Economics and Management Academy, Central University of Finance and Economics.
    59. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
    60. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    61. Li, Zhuo & Wen, Fenghua & Huang, Zhijian James, 2023. "Asymmetric response to earnings news across different sentiment states: The role of cognitive dissonance," Journal of Corporate Finance, Elsevier, vol. 78(C).
    62. Lv, Wendai & Qi, Jipeng, 2022. "Stock market return predictability: A combination forecast perspective," International Review of Financial Analysis, Elsevier, vol. 84(C).
    63. Zhikai Zhang & Yaojie Zhang & Yudong Wang & Qunwei Wang, 2024. "The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 557-584, April.
    64. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    65. Bi, Jia & Zhu, Yifeng, 2020. "Value at risk, cross-sectional returns and the role of investor sentiment," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 1-18.
    66. Bäumer, Marcus, 2020. "What matters to investment professionals in decision making? The role of soft factors in stock selection," EIKV-Schriftenreihe zum Wissens- und Wertemanagement, European Institute for Knowledge & Value Management (EIKV), Luxembourg, volume 44, number 44, June.
    67. Nianling Wang & Lijie Zhang & Zhuo Huang & Yong Li, 2021. "Asymmetric Correlations in Predicting Portfolio Returns," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 97-120, March.
    68. Riza Demirer & Konstantinos Gkillas & Christos Kountzakis & Amaryllis Mavragani, 2020. "Risk Appetite and Jumps in Realized Correlation," Mathematics, MDPI, vol. 8(12), pages 1-11, December.
    69. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    70. Chue, Timothy K. & Xu, Jin Karen, 2022. "Profitability, asset investment, and aggregate stock returns," Journal of Banking & Finance, Elsevier, vol. 143(C).
    71. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    72. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    73. Samuel YM Ze‐To, 2022. "Fundamental index aligned and excess market return predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 592-614, April.
    74. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    75. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Effect of Investor Sentiment on Gold Market Dynamics," Working Papers 201638, University of Pretoria, Department of Economics.
    76. Zheng, Yao & Osmer, Eric & Zu, Dingding, 2024. "Timing sentiment with style: Evidence from mutual funds," Journal of Banking & Finance, Elsevier, vol. 164(C).
    77. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    78. Li, Jun & Wang, Huijun & Yu, Jianfeng, 2018. "Aggregate Expected Investment Growth and Stock Market Returns," ADBI Working Papers 808, Asian Development Bank Institute.
    79. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    80. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2023. "Forecasting crude oil prices: A reduced-rank approach," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 698-711.
    81. Shrestha, Keshab & Philip, Sheena Sara Suresh & Khaw, Karren Lee-Hwei, 2024. "Impact of geopolitical risk on target debt ratio," Finance Research Letters, Elsevier, vol. 60(C).
    82. Seiler, Volker & Fanenbruck, Katharina Maria, 2021. "Acceptance of digital investment solutions: The case of robo advisory in Germany," Research in International Business and Finance, Elsevier, vol. 58(C).
    83. Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    84. Lin, Hai & Tao, Xinyuan & Wu, Chunchi, 2022. "Forecasting earnings with combination of analyst forecasts," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 133-159.
    85. Larissa Batrancea, 2021. "Empirical Evidence Regarding the Impact of Economic Growth and Inflation on Economic Sentiment and Household Consumption," JRFM, MDPI, vol. 14(7), pages 1-16, July.
    86. Jin, Zuben, 2024. "Business aspects in focus, investor underreaction and return predictability," Journal of Corporate Finance, Elsevier, vol. 84(C).
    87. Adrian Fernandez‐Perez & Raquel López, 2023. "The effect of macroeconomic news announcements on the implied volatility of commodities: The role of survey releases," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1499-1530, November.
    88. Wang, Gang-Jin & Xiong, Lu & Zhu, You & Xie, Chi & Foglia, Matteo, 2022. "Multilayer network analysis of investor sentiment and stock returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    89. Guo, Jiaqi & Li, Youwei & Zheng, Min, 2019. "Bottom-up sentiment and return predictability of the market portfolio," Finance Research Letters, Elsevier, vol. 29(C), pages 57-60.
    90. Chen, Zhongdong & Daves, Phillip R., 2018. "The January sentiment effect in the U.S. stock market," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 94-104.
    91. Gong, Xue & Lai, Ping & He, Mengxi & Wen, Danyan, 2024. "Climate risk and energy futures high frequency volatility prediction," Energy, Elsevier, vol. 307(C).
    92. Kwon, Kyung Yoon & Min, Byoung-Kyu & Sun, Chenfei, 2022. "Enhancing the profitability of lottery strategies," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 166-184.
    93. Zhen Cao & Jiancheng Shen & Xinbei Wei & Qunzi Zhang, 2023. "Anger in predicting the index futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 437-454, April.
    94. Yao Zheng & Eric Osmer & Liancun Zheng, 2020. "Can mutual funds time investor sentiment?," Review of Quantitative Finance and Accounting, Springer, vol. 54(4), pages 1449-1486, May.
    95. Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2024. "The Surprising Robustness of Partial Least Squares," Papers 2409.05713, arXiv.org.
    96. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    97. Yao-Tsung Wu & Chien-Hung Liu & Kuo-Hao Lin & Dun-Yao Ke, 2024. "Does media coverage matter for the performance of technical trading strategies? Evidence from Taiwan," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(1), pages 147-166, January.
    98. Rangan Gupta, 2018. "Manager Sentiment and Stock Market Volatility," Working Papers 201853, University of Pretoria, Department of Economics.
    99. Ma, Feng & Wu, Hanlin & Zeng, Qing, 2024. "Biodiversity and stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    100. Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
    101. Karam KIM & Doojin RYU, 2020. "Predictive ability of investor sentiment for the stock market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 33-46, December.
    102. Mengxi He & Yaojie Zhang & Yudong Wang & Danyan Wen, 2024. "Modelling and forecasting crude oil price volatility with climate policy uncertainty," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    103. Fuwei Jiang & Fujing Jin & Kejia Zhang, 2023. "Financial openness and profitability premium: Causal evidence from the Shanghai‐Hong Kong Stock Connect," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 451-483, March.
    104. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
    105. Kim Kaivanto & Peng Zhang, 2019. "Popular Music, Sentiment, and Noise Trading," Working Papers 279326509, Lancaster University Management School, Economics Department.
    106. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
    107. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Long, Jian-You & Zhou, Yang, 2023. "Forecasting stock market volatility under parameter and model uncertainty," Research in International Business and Finance, Elsevier, vol. 66(C).
    108. Chiara Limongi Concetto & Francesco Ravazzolo, 2019. "Optimism in Financial Markets: Stock Market Returns and Investor Sentiments," JRFM, MDPI, vol. 12(2), pages 1-14, May.
    109. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    110. Pablo Pastory y Camarasa & Martien Lamers, 2023. "Do Actions Follow Words? How bank sentiment predicts credit growth," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1073, Ghent University, Faculty of Economics and Business Administration.
    111. Onur Bayar & Emre Kesici, 2024. "The impact of social media on venture capital financing: evidence from Twitter interactions," Review of Quantitative Finance and Accounting, Springer, vol. 62(1), pages 195-224, January.
    112. Jonathan Fletcher, 2022. "Exploring the diversification benefits of US international equity closed-end funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 297-320, September.
    113. Fernandez-Perez, Adrian & Garel, Alexandre & Indriawan, Ivan, 2020. "Music sentiment and stock returns," Economics Letters, Elsevier, vol. 192(C).
    114. Xiaolu Wei & Hongbing Ouyang, 2023. "Forecasting Carbon Price Using Double Shrinkage Methods," IJERPH, MDPI, vol. 20(2), pages 1-20, January.
    115. Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
    116. Hao, Yijun & Su, Hao & Zhu, Xiaoneng, 2020. "Rare disaster concerns and economic fluctuations," Economics Letters, Elsevier, vol. 195(C).
    117. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    118. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    119. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    120. Shah, Syed Faisal & Albaity, Mohamed, 2022. "The role of trust, investor sentiment, and uncertainty on bank stock return performance: Evidence from the MENA region," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    121. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    122. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    123. Yongan Xu & Chao Liang, 2024. "Does extreme climate concern drive equity premiums? Evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    124. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
    125. Fameliti Stavroula & Skintzi Vasiliki, 2024. "Macroeconomic attention and commodity market volatility," Empirical Economics, Springer, vol. 67(5), pages 1967-2007, November.
    126. Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "The Predictive Power of Industrial Electricity Usage Revisited: Evidence from Nonparametric Causality Tests," Working Papers 201679, University of Pretoria, Department of Economics.
    127. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
    128. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    129. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    130. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
    131. Bissoondoyal-Bheenick, Emawtee & Do, Hung & Hu, Xiaolu & Zhong, Angel, 2022. "Sentiment and stock market connectedness: Evidence from the U.S. – China trade war," International Review of Financial Analysis, Elsevier, vol. 80(C).
    132. Tong Fang & Zhi Su & Libo Yin, 2021. "Does the green inspiration effect matter for stock returns? Evidence from the Chinese stock market," Empirical Economics, Springer, vol. 60(5), pages 2155-2176, May.
    133. Ghazi, Soroush & Schneider, Mark & Dorobiala, Zachary, 2024. "Speculative and non-speculative equity premia," Economics Letters, Elsevier, vol. 236(C).
    134. Birru, Justin & Young, Trevor, 2022. "Sentiment and uncertainty," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1148-1169.
    135. Huynh, Toan Luu Duc & Foglia, Matteo & Nasir, Muhammad Ali & Angelini, Eliana, 2021. "Feverish sentiment and global equity markets during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1088-1108.
    136. Yuna Hao & Behrang Vand & Benjamin Manrique Delgado & Simone Baldi, 2023. "Market Manipulation in Stock and Power Markets: A Study of Indicator-Based Monitoring and Regulatory Challenges," Energies, MDPI, vol. 16(4), pages 1-28, February.
    137. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2022. "The conditional impact of investor sentiment in global stock markets: A two-channel examination," Journal of Banking & Finance, Elsevier, vol. 138(C).
    138. Yun‐Huan Lee & Tzu‐Hsiang Liao & Hsiu‐Chuan Lee, 2022. "Overnight returns of industry exchange‐traded funds, investor sentiment, and futures market returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1114-1134, June.
    139. Bouteska, Ahmed & Kabir Hassan, M. & Gider, Zeynullah & Bataineh, Hassan, 2024. "The role of investor sentiment and market belief in forecasting V-shaped disposition effect: Evidence from a Bayesian learning process with DSSW model," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    140. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    141. Dong, Hang & Gil-Bazo, Javier, 2020. "Sentiment stocks," International Review of Financial Analysis, Elsevier, vol. 72(C).
    142. Andrea Buraschi & Paul Whelan, 2022. "Speculation, Sentiment, and Interest Rates," Management Science, INFORMS, vol. 68(3), pages 2308-2329, March.
    143. Massimo Guidolin & Erwin Hansen & Gabriel Cabrera, 2023. "Time-Varying Risk Aversion and International Stock Returns," BAFFI CAREFIN Working Papers 23203, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    144. Danish Ahmed & Yasir Shahab & Farid Ullah & Zhiwei Ye, 2020. "Investor sentiment and insurers’ financial stability: do sovereign ratings matter?," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(2), pages 281-312, April.
    145. Syed Jawad Hussain Shahzad & Clement Kweku Kyei & Rangan Gupta & Eric Olson, 2020. "Investor Sentiment and Dollar-Pound Exchange Rate Returns: Evidence from Over a Century of Data Using a Cross-Quantilogram Approach," Working Papers 202008, University of Pretoria, Department of Economics.
    146. Yuan, Xianghui & Li, Xiang, 2022. "Delta-hedging demand and intraday momentum: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    147. Cássio Zanatto & Margarida Catalão‐Lopes & Joaquim P. Pina & Inês Carrilho‐Nunes, 2023. "The impact of ESG news on the volatility of the Portuguese stock market—Does it change during recessions?," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5821-5832, December.
    148. Faiza Siddiqui & Yusheng Kong & Hyder Ali & Salma Naz, 2024. "Energy-Related Uncertainty and Idiosyncratic Return Volatility: Implications for Sustainable Investment Strategies in Chinese Firms," Sustainability, MDPI, vol. 16(17), pages 1-39, August.
    149. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    150. Haitham A. Al‐Zoubi & Jennifer A. O'Sullivan & Aktham I. Al‐Maghyereh & Brendan J. Lambe, 2023. "Disentangling Sentiment from Cyclicality in Firm Capital Structure," Abacus, Accounting Foundation, University of Sydney, vol. 59(2), pages 570-605, June.
    151. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    152. Baig, Ahmed & Blau, Benjamin M. & Sabah, Nasim, 2019. "Price clustering and sentiment in bitcoin," Finance Research Letters, Elsevier, vol. 29(C), pages 111-116.
    153. Bai, Chenjiang & Duan, Yuejiao & Liu, Congya & Qiu, Leiju, 2022. "International taxation sentiment and COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 63(C).
    154. Radi, Sherrihan & Gebka, Bartosz & Kallinterakis, Vasileios, 2024. "The wisdom of the madness of crowds: Investor herding, anti-herding, and stock-bond return correlation," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 966-995.
    155. Padma Kadiyala, 2022. "Response of ETF flows and long-run returns to investor sentiment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(4), pages 489-531, December.
    156. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    157. Lin, Qi & Lin, Xi, 2021. "Are the profitability and investment factors valid ICAPM risk factors? Pre-1963 evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    158. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
    159. Chen Gu & Xu Guo & Ruwan Adikaram & Kam C. Chan & Jing Lu, 2023. "Treasury return predictability and investor sentiment," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(4), pages 905-924, December.
    160. Ma, Tian & Leong, Wen Jun & Jiang, Fuwei, 2023. "A latent factor model for the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 87(C).
    161. Huang, Dashan & Jiang, Fuwei & Li, Kunpeng & Tong, Guoshi & Zhou, Guofu, 2023. "Are bond returns predictable with real-time macro data?," Journal of Econometrics, Elsevier, vol. 237(2).
    162. Supramono Supramono & Widhiastuti Wilis & I. Utami, 2017. "Market Reaction to Cabinet Reshuffle: The Indonesian Evidence," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 183-188.
    163. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    164. Lim, Bryan Y. & Wang, Jiaguo (George) & Yao, Yaqiong, 2018. "Time-series momentum in nearly 100 years of stock returns," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 283-296.
    165. Su, Hao & Ying, Chengwei & Zhu, Xiaoneng, 2022. "Disaster risk matters in the bond market," Finance Research Letters, Elsevier, vol. 47(PA).
    166. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    167. Demirovic, Amer & Kabiri, Ali & Tuckett, David & Nyman, Rickard, 2020. "A common risk factor and the correlation between equity and corporate bond returns," LSE Research Online Documents on Economics 116902, London School of Economics and Political Science, LSE Library.
    168. Paudel, Shishir & Silveri, Sabatino (Dino) & Wu, Mark, 2022. "Investor sentiment and asset prices: Evidence from the ex-day," Journal of Banking & Finance, Elsevier, vol. 139(C).
    169. Tianlun Fei & Xiaoquan Liu & Conghua Wen, 2023. "Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1594-1621, November.
    170. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
    171. Tan, Xiaoyu & Zhang, Zili & Zhao, Xuejun & Wang, Chengxiang, 2021. "Investor sentiment and limits of arbitrage: Evidence from Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 577-595.
    172. Chen, Yangyang & Goyal, Abhinav & Veeraraghavan, Madhu & Zolotoy, Leon, 2020. "Terrorist attacks, investor sentiment, and the pricing of initial public offerings," Journal of Corporate Finance, Elsevier, vol. 65(C).
    173. Sourav Prasad & Sabyasachi Mohapatra & Molla Ramizur Rahman & Amit Puniyani, 2022. "Investor Sentiment Index: A Systematic Review," IJFS, MDPI, vol. 11(1), pages 1-27, December.
    174. Mbarki, Imen & Omri, Abdelwahed & Naeem, Muhammad Abubakr, 2022. "From sentiment to systemic risk: Information transmission in Asia-Pacific stock markets," Research in International Business and Finance, Elsevier, vol. 63(C).
    175. Zongwu Cai & Pixiong Chen, 2024. "Online Investor Sentiment via Machine Learning," Mathematics, MDPI, vol. 12(20), pages 1-14, October.
    176. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
    177. Shu‐Lien Chang & Hsiu‐Chuan Lee & Donald Lien, 2022. "The global latent factor and international index futures returns predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 514-538, April.
    178. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
    179. Jiancheng Shen & Chen Chen & Zheng Liu, 2023. "Does environmental investment pay off?—portfolio analyses of the E in ESG during political conflicts and public health crises," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(S1), pages 107-131, December.
    180. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    181. Yu, Xing & Li, Yanyan & Gong, Xue & Zhang, Nan, 2022. "Evaluating the performance of futures hedging using factors-driven realized volatility," International Review of Financial Analysis, Elsevier, vol. 84(C).
    182. Konstantinos Gkillas & Rangan Gupta & Chi Keung Marco Lau & Muhammad Tahir Suleman, 2020. "Jumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movements," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(6), pages 1109-1127, April.
    183. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2017. "The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 51(C), pages 77-84.
    184. Can Huang & Yuqiang Cao & Meiting Lu & Yaowen Shan & Yizhou Zhang, 2023. "Messages in online stock forums and stock price synchronicity: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3011-3041, September.
    185. Ni, Yensen & Wu, Manhwa & Day, Min-Yuh & Huang, Paoyu, 2020. "Do sharp movements in oil prices matter for stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    186. Huang, Shuyang & Zeng, Ming, 2022. "Political sentiment and MAX effect," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    187. Zhifeng Dai & Jie Kang & Hua Yin, 2023. "Forecasting equity risk premium: A new method based on wavelet de‐noising," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4331-4352, October.
    188. Yamini Yadav & Pramod Kumar Naik, 2024. "Investors’ Irrational Sentiment and Stock Market Returns: A Quantile Regression Approach Using Indian Data," Business Perspectives and Research, , vol. 12(1), pages 45-64, January.
    189. Qadan, Mahmoud & Jacob, Maram, 2022. "The value premium and investors' appetite for risk," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 194-219.
    190. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    191. Islam, Mohd. Anisul, 2021. "Investor sentiment in the equity market and investments in corporate-bond funds," International Review of Financial Analysis, Elsevier, vol. 78(C).
    192. Mahmoudi, Nader & Docherty, Paul & Melia, Adrian, 2022. "Firm-level investor sentiment and corporate announcement returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    193. Adnen Ben Nasr & Matteo Bonato & Riza Demirer & Rangan Gupta, 2019. "Investor Sentiment and Crash Risk in Safe Havens," Journal of Economics and Behavioral Studies, AMH International, vol. 10(6), pages 97-108.
    194. Yuan Li & Yu Zhang, 2021. "Investor Sentiment, Idiosyncratic Risk, and Stock Price Premium: Evidence From Chinese Cross-Listed Companies," SAGE Open, , vol. 11(2), pages 21582440211, June.
    195. Chen, Wen, 2021. "Equity investor sentiment and bond market reaction: Test of overinvestment and capital flow hypotheses," Journal of Financial Markets, Elsevier, vol. 55(C).
    196. Tian Ma & Cunfei Liao & Fuwei Jiang, 2023. "Timing the factor zoo via deep learning: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 485-505, March.
    197. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    198. Kostopoulos, Dimitrios & Meyer, Steffen, 2018. "Disentangling investor sentiment: Mood and household attitudes towards the economy," Journal of Economic Behavior & Organization, Elsevier, vol. 155(C), pages 28-78.
    199. Chen, Rongda & Wang, Shengnan & Jin, Chenglu & Yu, Jingjing & Zhang, Xinyu & Zhang, Shuonan, 2023. "Comovements between multidimensional investor sentiment and returns on internet financial products," International Review of Financial Analysis, Elsevier, vol. 85(C).
    200. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    201. Amer Demirovic & Ali Kabiri & David Tuckett & Rickard Nyman, 2020. "A common risk factor and the correlation between equity and corporate bond returns," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 119-134, March.
    202. Tao, Ran & Brooks, Chris & Bell, Adrian R., 2020. "When is a MAX not the MAX? How news resolves information uncertainty," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 33-51.
    203. Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
    204. Fletcher, Jonathan, 2021. "International equity U.S. mutual funds and diversification benefits," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 246-257.
    205. Wang, Cheng & Han, Jing, 2023. "Prospect theory and mutual fund flows: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    206. Saji Thazhungal Govindan Nair, 2021. "On extreme value theory in the presence of technical trend: pre and post Covid-19 analysis of cryptocurrency markets," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 14(4), pages 533-561, December.
    207. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    208. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    209. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
    210. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    211. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    212. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    213. Papakyriakou, Panayiotis & Sakkas, Athanasios & Taoushianis, Zenon, 2019. "The impact of terrorist attacks in G7 countries on international stock markets and the role of investor sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 143-160.
    214. Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2025. "Quantile-Covariance Three-Pass Regression Filter," Working Papers 202501, University of California at Riverside, Department of Economics.
    215. Yu, Xing & Shen, Xilin & Li, Yanyan & Gong, Xue, 2023. "Selective hedging strategies for crude oil futures based on market state expectations," Global Finance Journal, Elsevier, vol. 57(C).
    216. Wang, Ningli & You, Wanhai, 2023. "New insights into the role of global factors in BRICS stock markets: A quantile cointegration approach," Economic Systems, Elsevier, vol. 47(2).
    217. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    218. Masud Alam, 2024. "Volatility in U.S. Housing Sector and the REIT Equity Return," The Journal of Real Estate Finance and Economics, Springer, vol. 69(3), pages 505-544, October.
    219. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.
    220. Qadan, Mahmoud & Aharon, David Y., 2019. "Can investor sentiment predict the size premium?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 10-26.
    221. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
    222. David A. Mascio & Frank J. Fabozzi & J. Kenton Zumwalt, 2021. "Market timing using combined forecasts and machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 1-16, January.
    223. Jie Ren & Hang Dong & Balaji Padmanabhan & Jeffrey V. Nickerson, 2021. "How does social media sentiment impact mass media sentiment? A study of news in the financial markets," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(9), pages 1183-1197, September.
    224. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    225. Park, Dojoon & Hahn, Jaehoon & Eom, Young Ho, 2024. "Predicting the equity premium with financial ratios: A comprehensive look over a long period in Korea," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
    226. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    227. Pedro Manuel Nogueira Reis & Carlos Pinho, 2021. "A Reappraisal of the Causal Relationship between Sentiment Proxies and Stock Returns," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 22(4), pages 420-442, October.
    228. Ma, Feng & Cao, Jiawei, 2023. "The Chinese equity premium predictability: Evidence from a long historical data," Finance Research Letters, Elsevier, vol. 53(C).
    229. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    230. Vitor Azevedo & Christoph Kaserer & Lucila M. S. Campos, 2021. "Investor sentiment and the time-varying sustainability premium," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 600-621, December.
    231. Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2018. "Predicting Stock Returns And Volatility With Investor Sentiment Indices: A Reconsideration Using A Nonparametric Causality†In†Quantiles Test," Bulletin of Economic Research, Wiley Blackwell, vol. 70(1), pages 74-87, January.
    232. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    233. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    234. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    235. Chen, Huimin (Amy) & Karim, Khondkar & Tao, Anqi, 2021. "The effect of suppliers' corporate social responsibility concerns on customers' stock price crash risk," Advances in accounting, Elsevier, vol. 52(C).
    236. Ye, Chuxin & Lv, Jiamin & Xue, Yinsong & Luo, Xingguo, 2023. "Intraday volatility predictability in china gold futures market: The case of last half-hour realized volatility forecasting," Finance Research Letters, Elsevier, vol. 58(PA).
    237. Sang Ik Seok & Hoon Cho & Chanhi Park & Doojin Ryu, 2019. "Do Overnight Returns Truly Measure Firm-Specific Investor Sentiment in the KOSPI Market?," Sustainability, MDPI, vol. 11(13), pages 1-14, July.
    238. Luo, Qin & Ma, Feng & Wang, Jiqian & Wu, You, 2024. "Changing determinant driver and oil volatility forecasting: A comprehensive analysis," Energy Economics, Elsevier, vol. 129(C).
    239. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    240. Qi Lin, 2020. "Idiosyncratic momentum and the cross‐section of stock returns: Further evidence," European Financial Management, European Financial Management Association, vol. 26(3), pages 579-627, June.
    241. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    242. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    243. Park, Yang-Ho, 2022. "Informed trading in foreign exchange futures: Payroll news timing," Journal of Banking & Finance, Elsevier, vol. 135(C).
    244. Tri Minh Phan, 2024. "Sentiment-semantic word vectors: A new method to estimate management sentiment," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-22, December.
    245. Ung, Sze Nie & Gebka, Bartosz & Anderson, Robert D.J., 2023. "Is sentiment the solution to the risk–return puzzle? A (cautionary) note," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    246. Qadan, Mahmoud, 2019. "Risk appetite, idiosyncratic volatility and expected returns," International Review of Financial Analysis, Elsevier, vol. 65(C).
    247. Chen, Rongda & Wei, Bo & Jin, Chenglu & Liu, Jia, 2021. "Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments," International Review of Financial Analysis, Elsevier, vol. 76(C).
    248. Fuwei Jiang & Wei Ning & Hao Xue, 2023. "Factor Timing with Investor Sentiment," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 401-437, November.
    249. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    250. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2015. "Market Sentiment and Paradigm Shifts," Research Paper Series 356, Quantitative Finance Research Centre, University of Technology, Sydney.
    251. Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018. "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, vol. 70(C), pages 472-483.
    252. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    253. Wang, Wenzhao, 2018. "Investor sentiment and the mean-variance relationship: European evidence," Research in International Business and Finance, Elsevier, vol. 46(C), pages 227-239.
    254. Pan, Wei-Fong, 2018. "Evidence of Investor Sentiment Contagion across Asset Markets," MPRA Paper 88561, University Library of Munich, Germany.
    255. Tim Bollerslev & Viktor Todorov & Lai Xu, 2014. "Tail Risk Premia and Return Predictability," CREATES Research Papers 2014-49, Department of Economics and Business Economics, Aarhus University.
    256. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
    257. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    258. Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
    259. Wenjie Ding & Khelifa Mazouz & Qingwei Wang, 2019. "Investor sentiment and the cross-section of stock returns: new theory and evidence," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 493-525, August.
    260. Guobin Fang & Xuehua Zhou, 2024. "Web Semantic Analysis of Investor Sentiment, Short Trading, and Stock Market Volatility," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 20(1), pages 1-35, January.
    261. Zhaoxing Gao & Ruey S. Tsay, 2023. "Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors," Papers 2307.07689, arXiv.org.
    262. Ferreira, Joaquim & Morais, Flávio, 2023. "Predict or to be predicted? A transfer entropy view between adaptive green markets, structural shocks and sentiment index," Finance Research Letters, Elsevier, vol. 56(C).
    263. Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
    264. Zhen Peng & Changsheng Hu, 2020. "Leveraged Trading, Irrational Sentiment and Sustainability in the Stock Market: Evidence from China," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    265. Meng, Bo & Vijh, Anand M., 2021. "Stock merger activity and industry performance," Journal of Banking & Finance, Elsevier, vol. 129(C).
    266. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    267. Chen, Zhenxi & Lien, Donald & Lin, Yaheng, 2021. "Sentiment: The bridge between financial markets and macroeconomy," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1177-1190.
    268. Chelikani, Surya & Marks, Joseph M. & Nam, Kiseok, 2024. "State-dependent intertemporal risk-return tradeoff: Further evidence," Journal of Economics and Business, Elsevier, vol. 130(C).
    269. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
    270. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    271. Chen, Yi-Wen & Chou, Robin K. & Lin, Chu-Bin, 2019. "Investor sentiment, SEO market timing, and stock price performance," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 28-43.
    272. St¨¦phane Chr¨¦tien & Manel Kammoun, 2019. "Mutual Fund Styles and Clientele-Specific Performance Evaluation," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(12), pages 1-89, December.
    273. Liu, Qingbai & Wang, Chuanjie & Zhang, Ping & Zheng, Kaixin, 2021. "Detecting stock market manipulation via machine learning: Evidence from China Securities Regulatory Commission punishment cases," International Review of Financial Analysis, Elsevier, vol. 78(C).
    274. Neenu C & T Mohamed Nishad, 2022. "Behavior of Financial Markets Around News Announcements: A Review Based on Bibliometric Analysis of Scientific Fields," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 14(2), pages 143-172, December.
    275. Xue Gong & Weiguo Zhang & Weijun Xu & Zhe Li, 2022. "Uncertainty index and stock volatility prediction: evidence from international markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-44, December.
    276. Hammami, Yacine & Zhu, Jie, 2020. "Understanding time-varying short-horizon predictability✰," Finance Research Letters, Elsevier, vol. 32(C).
    277. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    278. Brennan, M.J. & Taylor, Alex P., 2023. "Expected returns and risk in the stock market," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 276-300.
    279. Chen, Rongda & Huang, Jiahao & Jin, Chenglu & Yang, Yili & Chen, Bing, 2023. "Multidimensional attention to Fintech, trading behavior and stock returns," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 373-382.
    280. Guo, Haifeng & Wang, Ying & Wang, Bo & Ge, Yuanjing, 2022. "Does prospectus AE affect IPO underpricing? A content analysis of the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 1-12.
    281. Feng Zhao & Guofu Zhou & Xiaoneng Zhu, 2021. "Unspanned Global Macro Risks in Bond Returns," Management Science, INFORMS, vol. 67(12), pages 7825-7843, December.
    282. Sakariyahu, Rilwan & Lawal, Rodiat & Adigun, Rasheed & Paterson, Audrey & Johan, Sofia, 2024. "One crash, too many: Global uncertainty, sentiment factors and cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 94(C).
    283. Gaoshan Wang & Guangjin Yu & Xiaohong Shen, 2020. "The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach," Complexity, Hindawi, vol. 2020, pages 1-11, December.
    284. KhasadYahu ZarBabal & Jocelyn Evans, 2018. "Does wall street affect main street? examining potential spillovers from investor stock market sentiment to personal consumption expenditures," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 293-314, April.
    285. Weiguo Zhang & Xue Gong & Chao Wang & Xin Ye, 2021. "Predicting stock market volatility based on textual sentiment: A nonlinear analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1479-1500, December.
    286. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    287. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    288. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    289. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    290. Herculano, Miguel C. & Lütkebohmert, Eva, 2023. "Investor sentiment and global economic conditions," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 134-152.
    291. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    292. Nicolas Chatelais & Arthur Stalla-Bourdillon & Menzie D. Chinn, 2022. "Macroeconomic Forecasting using Filtered Signals from a Stock Market Cross Section," NBER Working Papers 30305, National Bureau of Economic Research, Inc.
    293. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    294. Shulin Shen & Yiyi Zhao & Jindong Pang, 2024. "Local Housing Market Sentiments and Returns: Evidence from China," The Journal of Real Estate Finance and Economics, Springer, vol. 68(3), pages 488-522, April.
    295. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    296. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    297. Han, Yufeng & Huang, Dashan & Huang, Dayong & Zhou, Guofu, 2022. "Expected return, volume, and mispricing," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1295-1315.
    298. Chen, Rongda & Xu, Guorui & Xu, Feng & Jin, Chenglu & Yu, Jingjing, 2022. "A clientele effect in online lending markets: Evidence from the comovement between investor sentiment and online lending rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    299. Taufiq Choudhry & Gishan Dissanaike & Ranadeva Jayasekera & Woo-Young Kang & Matthias Nnadi, 2021. "Loss sensitive investors and positively biased analysts in Hong Kong stock market," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1345-1371, November.
    300. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    301. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    302. Li, Jun & Wang, Huijun & Yu, Jianfeng, 2021. "Aggregate expected investment growth and stock market returns," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 618-638.
    303. Hadad, Elroi & Kedar-Levy, Haim, 2024. "The impact of retail investor sentiment on the conditional volatility of stocks and bonds: Evidence from the Tel-Aviv stock exchange," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1303-1313.
    304. Chuxuan Xiao & Winifred Huang & David P. Newton, 2024. "Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 979-1006, October.
    305. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    306. Li, Tangrong & Sun, Xuchu, 2023. "Predicting stock market returns using aggregate credit risk," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1087-1103.
    307. Rameeza Andleeb & Arshad Hassan, 2023. "Impact of Investor Sentiment on Contemporaneous and Future Equity Returns in Emerging Markets," SAGE Open, , vol. 13(3), pages 21582440231, August.
    308. Yigit Atilgan & K. Ozgur Demirtas & A. Doruk Gunaydin & Imra Kirli, 2023. "Average skewness in global equity markets," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 245-271, June.
    309. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
    310. Erdemlioglu, Deniz & Joliet, Robert, 2019. "Long-term asset allocation, risk tolerance and market sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 1-19.
    311. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    312. Arseny Gorbenko & Marcin Kacperczyk, 2023. "Short Interest and Aggregate Stock Returns: International Evidence," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(4), pages 691-733.
    313. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    314. Li, Xiaodan & Gong, Xue & Ge, Futing & Huang, Jingjing, 2024. "Forecasting stock volatility using pseudo-out-of-sample information," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 123-135.
    315. Wu, Qinin & Lu, Jing, 2020. "Air pollution, individual investors, and stock pricing in China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 267-287.
    316. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    317. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    318. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    319. Duan, Huayou & Zhao, Chenchen & Wang, Lu & Liu, Guangqiang, 2024. "The relationship between renewable energy attention and volatility: A HAR model with markov time-varying transition probability," Research in International Business and Finance, Elsevier, vol. 71(C).
    320. Xu, Hai-Chuan & Zhou, Wei-Xing, 2018. "A weekly sentiment index and the cross-section of stock returns," Finance Research Letters, Elsevier, vol. 27(C), pages 135-139.
    321. Fletcher, Jonathan, 2021. "Evaluating the performance of U.S. international equity closed-end funds," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    322. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    323. Ngoc Bao Vuong & Yoshihisa Suzuki, 2022. "The Moderating Effect of Market-Specific Factors on the Return Predictability of Investor Sentiment," SAGE Open, , vol. 12(3), pages 21582440221, July.
    324. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
    325. Zeng, Qing & Lu, Xinjie & Dong, Dayong & Li, Pan, 2022. "Category-specific EPU indices, macroeconomic variables and stock market return predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    326. Yuan Liao & Xinjie Ma & Andreas Neuhierl & Zhentao Shi, 2023. "Economic Forecasts Using Many Noises," Papers 2312.05593, arXiv.org, revised Dec 2023.
    327. Jia, Zhenzhen & Tiwari, Sunil & Zhou, Jianhua & Farooq, Muhammad Umar & Fareed, Zeeshan, 2023. "Asymmetric nexus between Bitcoin, gold resources and stock market returns: Novel findings from quantile estimates," Resources Policy, Elsevier, vol. 81(C).
    328. Gregory, Richard Paul, 2021. "What determines Manager and Investor Sentiment?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    329. Kim, Karam & Ryu, Doojin, 2022. "Sentiment changes and the Monday effect," Finance Research Letters, Elsevier, vol. 47(PB).
    330. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    331. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    332. Byun, Suk-Joon & Cho, Sangheum & Kim, Da-Hea, 2024. "Can a machine learn from behavioral biases? Evidence from stock return predictability of deep learning models," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    333. Le, Thai Hong & Luong, Anh Tram, 2022. "Dynamic spillovers between oil price, stock market, and investor sentiment: Evidence from the United States and Vietnam," Resources Policy, Elsevier, vol. 78(C).
    334. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    335. James R. Barth & Sunghoon Joo & Hyeongwoo Kim & Kang Bok Lee & Stevan Maglic & Xuan Shen, 2020. "Forecasting Net Charge-Off Rates of Banks: A PLS Approach," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 63, pages 2265-2301, World Scientific Publishing Co. Pte. Ltd..
    336. Ngoc Bao Vuong & Yoshihisa Suzuki, 2020. "Does Fear has Stronger Impact than Confidence on Stock Returns? The Case of Asia-Pacific Developed Markets," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 67(2), pages 157-175, June.
    337. Ruan, Qingsong & Wang, Zilin & Zhou, Yaping & Lv, Dayong, 2020. "A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China," Economic Modelling, Elsevier, vol. 88(C), pages 47-58.
    338. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    339. An, Suwei, 2023. "Essays on incentive contracts, M&As, and firm risk," Other publications TiSEM dd97d2f5-1c9d-47c5-ba62-f, Tilburg University, School of Economics and Management.
    340. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    341. Lin, Chu-Bin & Chou, Robin K. & Wang, George H.K., 2018. "Investor sentiment and price discovery: Evidence from the pricing dynamics between the futures and spot markets," Journal of Banking & Finance, Elsevier, vol. 90(C), pages 17-31.
    342. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    343. Cheema, Arbab K. & Eshraghi, Arman & Wang, Qingwei, 2023. "Macroeconomic news and price synchronicity," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 390-412.
    344. Zaremba, Adam & Szyszka, Adam & Karathanasopoulos, Andreas & Mikutowski, Mateusz, 2021. "Herding for profits: Market breadth and the cross-section of global equity returns," Economic Modelling, Elsevier, vol. 97(C), pages 348-364.
    345. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    346. He, Zhifang, 2023. "Geopolitical risks and investor sentiment: Causality and TVP-VAR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    347. Ma, Yao & Yang, Baochen & Ye, Tao, 2024. "Quality acceleration and cross-sectional returns: Empirical evidence," Research in International Business and Finance, Elsevier, vol. 69(C).
    348. Barroso, Pedro & Detzel, Andrew, 2021. "Do limits to arbitrage explain the benefits of volatility-managed portfolios?," Journal of Financial Economics, Elsevier, vol. 140(3), pages 744-767.
    349. Chen, Rongda & Wang, Shengnan & Ye, Mengya & Jin, Chenglu & Ren, He & Chen, Shu, 2022. "Cross-Market Investor Sentiment of Energy Futures and Return Comovements," Finance Research Letters, Elsevier, vol. 49(C).
    350. Gady Jacoby & Chi Liao & Nanying Lin & Lei Lu, 2024. "Sentiment and the cross‐section of expected stock returns," The Financial Review, Eastern Finance Association, vol. 59(2), pages 459-485, May.
    351. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    352. John A. Doukas & Xiao Han, 2021. "Sentiment‐scaled CAPM and market mispricing," European Financial Management, European Financial Management Association, vol. 27(2), pages 208-243, March.
    353. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.
    354. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
    355. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    356. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    357. Guo, Haifeng & Hung, Chi-Hsiou D. & Kontonikas, Alexandros, 2022. "The Fed and the stock market: A tale of sentiment states," Journal of International Money and Finance, Elsevier, vol. 128(C).
    358. Shi, Qi, 2023. "The RP-PCA factors and stock return predictability: An aligned approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    359. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    360. Zhu, Zhaobo & Ji, Qiang & Sun, Licheng & Zhai, Pengxiang, 2020. "Oil price shocks, investor sentiment, and asset pricing anomalies in the oil and gas industry," International Review of Financial Analysis, Elsevier, vol. 70(C).
    361. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    362. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.
    363. Qiang Bu & Odd J. Stalebrink, 2020. "Can fund sentiment beta predict future performance?," Journal of Asset Management, Palgrave Macmillan, vol. 21(6), pages 524-534, October.
    364. Zhang, Teng & Li, Jiaqi & Xu, Zhiwei, 2024. "Speculative trading, stock returns and asset pricing anomalies," Emerging Markets Review, Elsevier, vol. 61(C).
    365. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    366. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2021. "Stock Market’s responses to intraday investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    367. Hai Lin & Pengfei Liu & Cheng Zhang, 2023. "The trend premium around the world: Evidence from the stock market," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 317-358, June.
    368. Nizar Raissi & Sahbi Missaoui, 2015. "Role of investor sentiment in financial markets: an explanation by behavioural finance approach," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 5(4), pages 362-401.
    369. Makridis, Christos A. & Schloetzer, Jason D., 2023. "Extreme local temperatures lower expressed sentiment about U.S. economic conditions with implications for the stock returns of local firms," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    370. Cao, Charles & Simin, Timothy & Xiao, Han, 2020. "Predicting the equity premium with the implied volatility spread," Journal of Financial Markets, Elsevier, vol. 51(C).
    371. Guettler, Andre & Hable, Patrick & Launhardt, Patrick & Miebs, Felix, 2023. "Aggregate insider trading in the S&P 500 and the predictability of international equity premia," Finance Research Letters, Elsevier, vol. 54(C).
    372. Qu, Hui & Li, Guo, 2023. "Multi-perspective investor attention and oil futures volatility forecasting," Energy Economics, Elsevier, vol. 119(C).
    373. Zhou, Xuemei & Liu, Qiang & Guo, Shuxin, 2021. "Do overnight returns explain firm-specific investor sentiment in China?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 451-477.
    374. Ahmed Bouteska & Taimur Sharif & Mohammad Zoynul Abedin, 2024. "Does investor sentiment create value for asset pricing? An empirical investigation of the KOSPI‐listed firms," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3487-3509, July.
    375. Cao, Charles & Simin, Timothy & Xiao, Han, 2019. "Predicting the equity premium with the implied volatility spread," MPRA Paper 103651, University Library of Munich, Germany.
    376. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    377. Sapkota, Niranjan & Grobys, Klaus, 2023. "Fear sells: On the sentiment deceptions and fundraising success of initial coin offerings," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    378. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    379. Lao, Jiashun & Nie, He & Jiang, Yonghong, 2018. "Revisiting the investor sentiment–stock returns relationship: A multi-scale perspective using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 420-427.
    380. Stefano Cassella & Huseyin Gulen, 2018. "Extrapolation Bias and the Predictability of Stock Returns by Price-Scaled Variables," The Review of Financial Studies, Society for Financial Studies, vol. 31(11), pages 4345-4397.
    381. Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie & Wang, Qunwei, 2024. "Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors," Energy Economics, Elsevier, vol. 133(C).
    382. Jian Chen & Yangshu Liu, 2020. "Bid and ask prices of index put options: Which predicts the underlying stock returns?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1337-1353, September.
    383. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    384. Naeem, Muhammad Abubakr & Senthilkumar, Arunachalam & Arfaoui, Nadia & Mohnot, Rajesh, 2024. "Mapping fear in financial markets: Insights from dynamic networks and centrality measures," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    385. Jeroen V.K. Rombouts & Lars Stentoft & Francesco Violante, 2017. "Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability," CREATES Research Papers 2017-10, Department of Economics and Business Economics, Aarhus University.
    386. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    387. Dang, Man & Puwanenthiren, Premkanth & Nguyen, Manh Toan & Hoang, Viet Anh & Mazur, Mieszko & Henry, Darren, 2022. "Does managerial tone matter for stock liquidity? Evidence from textual disclosures," Finance Research Letters, Elsevier, vol. 48(C).
    388. Bouteska, Ahmed & Cardillo, Giovanni & Harasheh, Murad, 2023. "Is it all about noise? Investor sentiment and risk nexus: evidence from China," Finance Research Letters, Elsevier, vol. 57(C).
    389. Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
    390. Xiao Han & Nikolaos Sakkas & Jo Danbolt & Arman Eshraghi, 2022. "Persistence of investor sentiment and market mispricing," The Financial Review, Eastern Finance Association, vol. 57(3), pages 617-640, August.
    391. Zaremba, Adam & Szyszka, Adam & Long, Huaigang & Zawadka, Dariusz, 2020. "Business sentiment and the cross-section of global equity returns," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    392. Shrestha, Keshab & Naysary, Babak, 2023. "ESG and economic policy uncertainty: A wavelet application," Finance Research Letters, Elsevier, vol. 58(PD).
    393. Zhang, Xinyue & Bissoondoyal-Bheenick, Emawtee & Zhong, Angel, 2023. "Investor sentiment and stock market anomalies in Australia," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 284-303.
    394. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    395. Wang, Jingya & Taylor, Alex P., 2024. "Predicting consumption-wealth ratio changes and stock market returns," Research in International Business and Finance, Elsevier, vol. 71(C).
    396. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    397. Zhu, Zhaobo & Sun, Licheng & Yung, Kenneth, 2020. "Fundamental strength strategy: The role of investor sentiment versus limits to arbitrage," International Review of Financial Analysis, Elsevier, vol. 71(C).
    398. Niall O’Sullivan & Sheng Zhu & Jason Foran, 2019. "Sentiment versus liquidity pricing effects in the cross-section of UK stock returns," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 317-329, July.
    399. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    400. Kim Kaivanto & Peng Zhang, 2019. "Investor Sentiment as a Predictor of Market Returns," Working Papers 268005798, Lancaster University Management School, Economics Department.
    401. Max Schreder & Pawel Bilinski, 2022. "Information Quality and the Expected Rate of Return: A Structural Equation Modelling Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(2), pages 139-170, June.
    402. Sun, Licheng & Najand, Mohammad & Shen, Jiancheng, 2016. "Stock return predictability and investor sentiment: A high-frequency perspective," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 147-164.
    403. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    404. Suardi, Sandy & Rasel, Atiqur Rahman & Liu, Bin, 2022. "On the predictive power of tweet sentiments and attention on bitcoin," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 289-301.
    405. Ding, Rui & Guo, Jintong & Zhang, Min, 2024. "Practice a poker face: Manager emotion and investor sentiment," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    406. Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.
    407. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    408. Chiu, Mei Choi & Wong, Hoi Ying & Zhao, Jing, 2018. "Dynamic safety first expected utility model," European Journal of Operational Research, Elsevier, vol. 271(1), pages 141-154.
    409. Zongwu Cai & Pixiong Chen, 2022. "New Online Investor Sentiment and Asset Returns," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202216, University of Kansas, Department of Economics, revised Nov 2022.
    410. Chen, Zhonglu & Liang, Chao & Umar, Muhammad, 2021. "Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility?," Resources Policy, Elsevier, vol. 74(C).
    411. Bank, Matthias & Insam, Franz, 2019. "Risk premium contributions of the Fama and French mimicking factors," Finance Research Letters, Elsevier, vol. 29(C), pages 347-356.
    412. Lu Wang & Shan Li & Chao Liang, 2024. "Exploring the impact of oil security attention on oil volatility: A new perspective," International Finance, Wiley Blackwell, vol. 27(1), pages 61-80, April.
    413. Szymon Lis, 2024. "Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence," Papers 2411.13180, arXiv.org.
    414. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.
    415. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    416. Haibin Xie & Shouyang Wang, 2018. "Timing the market: the economic value of price extremes," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-24, December.
    417. Wu, Qinqin & Hao, Ying & Lu, Jing, 2017. "Investor sentiment, idiosyncratic risk, and mispricing of American Depository Receipt," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 1-14.
    418. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
    419. Guohao Tang & Fuwei Jiang & Xinlin Qi & Nan Huang, 2021. "It takes two to tango: Fundamental timing in stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5259-5277, October.
    420. Lee, Geul & Ryu, Doojin, 2024. "Investor sentiment or information content? A simple test for investor sentiment proxies," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    421. Chen Gu & Denghui Chen & Raluca Stan, 2021. "Investor sentiment and the market reaction to macroeconomic news," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1412-1426, September.
    422. Chen, Jia & Yi, Xingjian & Liu, Hao, 2024. "Asset redeployability and firm value amidst the COVID-19 pandemic: A real options perspective," International Review of Financial Analysis, Elsevier, vol. 94(C).

  9. Han, Yufeng & Yang, Ke & Zhou, Guofu, 2013. "A New Anomaly: The Cross-Sectional Profitability of Technical Analysis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1433-1461, October.

    Cited by:

    1. Chen, Kuan-Hau & Su, Xuan-Qi & Lin, Li-Feng & Shih, Yi-Cheng, 2021. "Profitability of moving-average technical analysis over the firm life cycle: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    2. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    3. Eom, Cheoljun & Park, Jong Won, 2023. "Price behavior of small-cap stocks and momentum: A study using principal component momentum," Research in International Business and Finance, Elsevier, vol. 65(C).
    4. Ding, Wenjie & Mazouz, Khelifa & Wang, Qingwei, 2021. "Volatility timing, sentiment, and the short-term profitability of VIX-based cross-sectional trading strategies," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 42-56.
    5. Czudaj Robert L., 2020. "The role of uncertainty on agricultural futures markets momentum trading and volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-39, June.
    6. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    7. Matthew Lorig & Zhou Zhou & Bin Zou, 2017. "A Mathematical Analysis of Technical Analysis," Papers 1710.09476, arXiv.org, revised Feb 2019.
    8. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2021. "Economic news and the cross-section of commodity futures returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    9. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2021. "Financial news and CDS spreads," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    10. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    11. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    12. Haibin Xie & Shouyang Wang, 2015. "Risk-return trade-off, information diffusion, and U.S. stock market predictability," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-20, December.
    13. Anghel, Dan Gabriel, 2021. "Data Snooping Bias in Tests of the Relative Performance of Multiple Forecasting Models," Journal of Banking & Finance, Elsevier, vol. 126(C).
    14. Yajie Yang & Longfeng Zhao & Lin Chen & Chao Wang & Jihui Han, 2021. "Portfolio optimization with idiosyncratic and systemic risks for financial networks," Papers 2111.11286, arXiv.org.
    15. Ansari Saleh Ahmar, 2019. "Sutte Indicator: an approach to predict the direction of stock market movements," Papers 1903.11642, arXiv.org.
    16. Zhang, Manqing & Ma, Yao & Yang, Baochen & Fan, Ying, 2024. "The change in salience and the cross-section of stock returns: Empirical evidence from China A-shares," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    17. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    18. Huang, Jing-Zhi & Huang, Zhijian (James), 2020. "Testing moving average trading strategies on ETFs," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 16-32.
    19. Keith S. K. Lam & Liang Dong & Bo Yu, 2019. "Value Premium and Technical Analysis: Evidence from the China Stock Market," Economies, MDPI, vol. 7(3), pages 1-21, September.
    20. Gu, Ming & Sun, Minxing & Xiong, Zhitao & Xu, Weike, 2024. "Market volatility and the trend factor," Finance Research Letters, Elsevier, vol. 65(C).
    21. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    22. Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2024. "Forecasting the price of oil: A cautionary note," Journal of Commodity Markets, Elsevier, vol. 33(C).
    23. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    24. Demir Bektić & Tobias Regele, 2018. "Exploiting uncertainty with market timing in corporate bond markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 79-92, March.
    25. Eric Andr'e & Guillaume Coqueret, 2020. "Dirichlet policies for reinforced factor portfolios," Papers 2011.05381, arXiv.org, revised Jun 2021.
    26. Ma, Yao & Yang, Baochen & Li, Jinyong & Shen, Yue, 2023. "Trend information and cross-sectional returns: The role of analysts," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    27. Zaremba, Adam & Czapkiewicz, Anna, 2017. "The cross section of international government bond returns," Economic Modelling, Elsevier, vol. 66(C), pages 171-183.
    28. Chung, Chien-Ping & Chien, Cheng-Yi & Huang, Chia-Hsin & Lee, Hsiu-Chuan, 2021. "Foreign institutional ownership and the effectiveness of technical analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 86-96.
    29. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2017. "Time series momentum and moving average trading rules," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 405-421, March.
    30. Ma, Yao & Yang, Baochen & Su, Yunpeng, 2021. "Stock return predictability: Evidence from moving averages of trading volume," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    31. Guillaume Chevalier & Guillaume Coqueret & Thomas Raffinot, 2022. "Supervised portfolios," Post-Print hal-04144588, HAL.
    32. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    33. Ma, Yao & Yang, Baochen & Su, Yunpeng, 2020. "Technical trading index, return predictability and idiosyncratic volatility," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 879-900.
    34. Cakici, Nusret & Zaremba, Adam & Bianchi, Robert J. & Pham, Nga, 2021. "False discoveries in the anomaly research: New insights from the Stock Exchange of Melbourne (1927–1987)," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    35. Mohammed Bouasabah & Oshamah Ibrahim Khalaf, 2023. "A Technical Indicator for a Short-term Trading Decision in the NASDAQ Market," Advances in Decision Sciences, Asia University, Taiwan, vol. 27(3), pages 1-13, September.
    36. Ahmar, Ansari Saleh, 2017. "Predicting Movement of Stock of Apple Inc. using Sutte Indicator," INA-Rxiv pcxr5, Center for Open Science.
    37. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    38. Paskalis Glabadanidis, 2015. "Market Timing With Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 387-425, September.
    39. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    40. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    41. Jukka Ilomäki, 2018. "Risk and return of a trend-chasing application in financial markets: an empirical test," Risk Management, Palgrave Macmillan, vol. 20(3), pages 258-272, August.
    42. Mendes, Fernando Henrique de Paula e Silva & Caldeira, João Frois & Moura, Guilherme Valle, 2018. "Evidence of Bull and Bear Markets in the Bovespa index: An application of Markovian regime-switching Models with Duration Dependence," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
    43. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    44. Han, Yufeng & Hu, Ting & Yang, Jian, 2016. "Are there exploitable trends in commodity futures prices?," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 214-234.
    45. Paskalis Glabadanidis, 2017. "Timing the Market with a Combination of Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 353-394, September.
    46. Urquhart, Andrew & Zhang, Hanxiong, 2019. "The performance of technical trading rules in Socially Responsible Investments," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 397-411.
    47. Ko, Kuan-Cheng & Lin, Shinn-Juh & Su, Hsiang-Ju & Chang, Hsing-Hua, 2014. "Value investing and technical analysis in Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 14-36.
    48. Zhang Enguang & Ma He, 2023. "An Empirical Study on Chinese Futures Market Based on Bollinger Bands Strategy and R," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 12(4), pages 1-1.
    49. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    50. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    51. Robert Hudson & Andrew Urquhart, 2021. "Technical trading and cryptocurrencies," Annals of Operations Research, Springer, vol. 297(1), pages 191-220, February.
    52. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2022. "Economic importance of correlations for energy and other commodities," Energy Economics, Elsevier, vol. 107(C).
    53. Jin, Xiaoye, 2022. "Testing technical trading strategies on China's equity ETFs: A skewness perspective," Emerging Markets Review, Elsevier, vol. 51(PA).
    54. YuZhi Chen & Yi Fang & XinYue Li & Jian Wei, 2023. "A factor pricing model based on double moving average strategy," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    55. Joseph Zhi Bin Ling & Albert K. Tsui & Zhaoyong Zhang, 2021. "Trading Macro-Cycles of Foreign Exchange Markets Using Hybrid Models," Sustainability, MDPI, vol. 13(17), pages 1-20, September.
    56. Zakamulin, Valeriy & Giner, Javier, 2023. "Optimal trend-following with transaction costs," International Review of Financial Analysis, Elsevier, vol. 90(C).
    57. Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
    58. Achim BACKHAUS & Aliya ZHAKANOVA ISIKSAL, 2016. "The Impact of Momentum Factors on Multi Asset Portfolio," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 146-169, December.
    59. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.
    60. Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017. "Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?," IEAS Working Paper : academic research 17-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    61. Cepoi, Cosmin-Octavian & Anghel, Dan-Gabriel & Pop, Ionuţ Daniel, 2021. "Asymmetries and flight-to-safety effects in the price discovery process of cross-listed stocks," Economic Modelling, Elsevier, vol. 98(C), pages 302-318.
    62. Ansari Saleh Ahmar & Abdul Rahman & Andi Nurani Mangkawani Arifin & Alfatih Abqary Ahmar, 2017. "Predicting movement of stock of “Y” using Sutte Indicator," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1347123-134, January.
    63. Ansari Saleh Ahmar, 2017. "Sutte Indicator: A Technical Indicator in Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 223-226.
    64. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
    65. Szymon Lis, 2024. "Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence," Papers 2411.13180, arXiv.org.
    66. Ikhlaas Gurrib & Firuz Kamalov & Olga Starkova & Adham Makki & Anita Mirchandani & Namrata Gupta, 2023. "Performance of Equity Investments in Sustainable Environmental Markets," Sustainability, MDPI, vol. 15(9), pages 1-28, May.
    67. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2017. "Does Financial News Predict Stock Returns? New Evidence from Islamic and Non-Islamic Stocks," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 24-45.
    68. Dat Mai, 2024. "StockGPT: A GenAI Model for Stock Prediction and Trading," Papers 2404.05101, arXiv.org, revised Oct 2024.
    69. Zhaobo Zhu & Licheng Sun, 2024. "When Buffett Meets Bollinger: An Integrated Approach to Fundamental and Technical Analysis," Post-Print hal-04703041, HAL.

  10. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.

    Cited by:

    1. López Gaviria, José Ignacio, 2019. "Predictibilidad del mercado accionario colombiano," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 91, pages 117-150, July.
    2. James Nguyen & Wei-Xuan Li & Clara Chia-Sheng Chen, 2022. "Mean Reversions in Major Developed Stock Markets: Recent Evidence from Unit Root, Spectral and Abnormal Return Studies," JRFM, MDPI, vol. 15(4), pages 1-20, April.
    3. Chiang, Thomas C., 2021. "Spillovers of U.S. market volatility and monetary policy uncertainty to global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    5. Li, Xiyang & Chen, Xiaoyue & Li, Bin & Singh, Tarlok & Shi, Kan, 2022. "Predictability of stock market returns: New evidence from developed and developing countries," Global Finance Journal, Elsevier, vol. 54(C).
    6. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    7. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    8. Carl Remlinger & Bri`ere Marie & Alasseur Cl'emence & Joseph Mikael, 2021. "Expert Aggregation for Financial Forecasting," Papers 2111.15365, arXiv.org, revised Jul 2023.
    9. Boriss Siliverstovs, 2016. "International Stock Return Predictability: On the Role of the United States in Bad and Good Times," KOF Working papers 16-408, KOF Swiss Economic Institute, ETH Zurich.
    10. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    11. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    12. Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.
    13. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    14. Srivastava, Sasha & Lin, Hai & Premachandra, Inguruwatte M. & Roberts, Helen, 2016. "Global risk spillover and the predictability of sovereign CDS spread: International evidence," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 371-390.
    15. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    16. Chen, Xiaoyu & Chiang, Thomas C., 2020. "Empirical investigation of changes in policy uncertainty on stock returns—Evidence from China’s market," Research in International Business and Finance, Elsevier, vol. 53(C).
    17. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    18. Bailey, Warren B. & Cao, Xiaping & Yang, Zhenyi & Zhou, Sili, 2024. "Who leads and who follows? The cross-border peer effect in investment by Chinese and US firms," Journal of International Economics, Elsevier, vol. 147(C).
    19. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Thuraisamy, Kannan & Westerlund, Joakim, 2016. "Price discovery and asset pricing," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 224-235.
    20. Sarwar, Ghulam, 2017. "Examining the flight-to-safety with the implied volatilities," Finance Research Letters, Elsevier, vol. 20(C), pages 118-124.
    21. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.
    22. Das, Sonali & Demirer, Riza & Gupta, Rangan & Mangisa, Siphumlile, 2019. "The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 132-147.
    23. Ke-Li Xu & Junjie Guo, 2021. "A New Test for Multiple Predictive Regression," CAEPR Working Papers 2022-001 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    24. Ronit Mukherji, 2015. "Stock Market Efficiency in Developing Economies," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(4), pages 402-429, November.
    25. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2014. "Sticky prices or economically-linked economies: The case of forecasting the Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 95-109.
    26. David A. Mascio & Marat Molyboga & Frank J. Fabozzi, 2023. "The battle of the factors: Macroeconomic variables or investor sentiment?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2280-2291, December.
    27. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can machine learning help to select portfolios of mutual funds?," Economics Working Papers 1772, Department of Economics and Business, Universitat Pompeu Fabra.
    28. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    29. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
    30. Pan, Zhiyuan & Shuai, Jiangyu & Liang, Zhilei & Sun, Xianchao, 2022. "Jump dynamics, spillover effect and option valuation," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    31. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    32. Seyedeh Fatemeh Razmi & Bahareh Ramezanian Bajgiran & Seyed Mohammad Javad Razmi & Kiana Baensaf Oroumieh, 2020. "The Effects of External Uncertainties against Monetary Policy Uncertainty on IRANIAN Stock Return Volatility Using GARCH-MIDAS Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 278-281.
    33. Reinhold Heinlein & Scott M. R. Mahadeo, 2021. "Oil and US stock market shocks: implications for Canadian equities," Working Papers in Economics & Finance 2021-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    34. Mei, Dexiang & Zeng, Qing & Zhang, Yaojie & Hou, Wenjing, 2018. "Does US Economic Policy Uncertainty matter for European stock markets volatility?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 215-221.
    35. Dohyun Chun & Jongho Kang & Jihun Kim, 2024. "Forecasting returns with machine learning and optimizing global portfolios: evidence from the Korean and U.S. stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-30, December.
    36. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    37. Mingwei Sun & Paskalis Glabadanidis, 2022. "Can technical indicators predict the Chinese equity risk premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 114-142, March.
    38. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    39. Berardi, Andrea & Plazzi, Alberto, 2022. "Dissecting the yield curve: The international evidence," Journal of Banking & Finance, Elsevier, vol. 134(C).
    40. Dashan Huang & Jiangyuan Li & Liyao Wang & Guofu Zhou, 2020. "Time series momentum: Is it there?," CEMA Working Papers 717, China Economics and Management Academy, Central University of Finance and Economics.
    41. Juan M. Londono & Nancy R. Xu, 2021. "The Global Determinants of International Equity Risk Premiums," International Finance Discussion Papers 1318, Board of Governors of the Federal Reserve System (U.S.).
    42. Hadhri, Sinda & Ftiti, Zied, 2017. "Stock return predictability in emerging markets: Does the choice of predictors and models matter across countries?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 39-60.
    43. Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
    44. Min Chen & Zhaobo Zhu & Peiwen Han & Bo Chen & Jia Liu, 2022. "Economic policy uncertainty and analyst behaviours: Evidence from the United Kingdom," Post-Print hal-03628930, HAL.
    45. Apergis, Nicholas & Gupta, Rangan, 2017. "Can (unusual) weather conditions in New York predict South African stock returns?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 377-386.
    46. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    47. Takuro Hidaka & Yuta Saito & Jun Sakamoto, 2021. "Historical Relationships and International Market Return Predictability: The Role of the UK in the Former British Colonies, Protectorates and Mandates," Discussion Papers in Economics and Business 21-08-Rev., Osaka University, Graduate School of Economics, revised Oct 2023.
    48. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    49. Chen, Zhenhua & Liu, Zhenya & Teka, Hanen & Zhang, Yifan, 2022. "Smart money in China's A-share market: Evidence from big data," Research in International Business and Finance, Elsevier, vol. 61(C).
    50. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2016. "Steel scrap and equity market in Japan," Resources Policy, Elsevier, vol. 47(C), pages 115-124.
    51. Labidi, Chiaz & Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Bekiros, Stelios, 2018. "Quantile dependence between developed and emerging stock markets aftermath of the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 179-211.
    52. Cenedese, Gino & Mallucci, Enrico, 2016. "What moves international stock and bond markets?," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 94-113.
    53. Sui, Cong & Wang, Shuhan & Zheng, Wei, 2024. "Sentiment as a shipping market predictor: Testing market-specific language models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).
    54. Khurshid M. Kiani, 2016. "On Modelling and Forecasting Predictable Components in European Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 487-502, October.
    55. Christina Christou & Rangan Gupta, 2016. "Forecasting Equity Premium in a Panel of OECD Countries: The Role of Economic Policy Uncertainty," Working Papers 201622, University of Pretoria, Department of Economics.
    56. Maryam Abid & Danish Ahmed Siddique, 2020. "Impact of Financial Market Uncertainty on Market Returns: A Global Analysis," Business and Economic Research, Macrothink Institute, vol. 10(3), pages 216-244, September.
    57. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    58. Narongdech Thakerngkiat & Hung T. Nguyen & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2021. "Do accounting information and market environment matter for cross‐asset predictability?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4389-4434, September.
    59. Narayan, Paresh Kumar, 2019. "Can stale oil price news predict stock returns?," Energy Economics, Elsevier, vol. 83(C), pages 430-444.
    60. David Haab & Thomas Nitschka, 2017. "Predicting returns on asset markets of a small, open economy and the influence of global risks," Working Papers 2017-14, Swiss National Bank.
    61. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2015. "International Stock Return Predictability: Is the Role of U.S. Time-Varying?," Working Papers 201524, University of Pretoria, Department of Economics.
    62. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
    63. Zhang, Yaojie & He, Mengxi & Liao, Cunfei & Wang, Yudong, 2023. "Climate risk exposure and the cross-section of Chinese stock returns," Finance Research Letters, Elsevier, vol. 55(PB).
    64. Narayan, Paresh Kumar, 2018. "Profitability of technology-investing Islamic and non-Islamic stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 52(C), pages 70-81.
    65. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    66. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.
    67. Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar & Alagidede, Imhotep Paul & Gil-Alana, Luis Alberiko, 2022. "Re-examination of risk-return dynamics in international equity markets and the role of policy uncertainty, geopolitical risk and VIX: Evidence using Markov-switching copulas," Finance Research Letters, Elsevier, vol. 47(PA).
    68. Huang, MeiChi & Wu, Chu-Hua & Cheng, I-Shan, 2021. "A truly global crisis? Evidence from contagion dependence across international REIT markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    69. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
    70. Sakemoto, Ryuta, 2023. "The long-run risk premium in the intertemporal CAPM: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    71. Lee, Hsiu-Chuan & Lee, Yun-Huan & Nguyen, Cuong, 2023. "Tail comovements of implied volatility indices and global index futures returns predictability," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    72. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
    73. Malakhov, Alexey & Riley, Timothy B. & Yan, Qing, 2024. "Do hedge funds bet against beta?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1507-1525.
    74. Chen, Bin-xia & Sun, Yan-lin, 2022. "The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    75. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    76. Nakagawa, Kei & Sakemoto, Ryuta, 2022. "Cryptocurrency network factors and gold," Finance Research Letters, Elsevier, vol. 46(PB).
    77. Shirui Wang & Tianyang Zhang, 2024. "Predictability of commodity futures returns with machine learning models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 302-322, February.
    78. Hyeon-Seok Kim & Hui-Sang Kim & Sun-Yong Choi, 2024. "Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis," Energies, MDPI, vol. 17(5), pages 1-24, February.
    79. Weijia Peng & Chun Yao, 2023. "Sector-level equity returns predictability with machine learning and market contagion measure," Empirical Economics, Springer, vol. 65(4), pages 1761-1798, October.
    80. Yi Cao & Xiaoquan Liu & Jia Zhai & Shan Hua, 2022. "A two‐stage Bayesian network model for corporate bankruptcy prediction," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 455-472, January.
    81. Billio, Monica & Lo, Andrew W. & Pelizzon, Loriana & Getmansky, Mila & Zareei, Abalfazl, 2021. "Global realignment in financial market dynamics: Evidence from ETF networks," SAFE Working Paper Series 304, Leibniz Institute for Financial Research SAFE.
    82. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2023. "Tail risks and forecastability of stock returns of advanced economies: evidence from centuries of data," The European Journal of Finance, Taylor & Francis Journals, vol. 29(4), pages 466-481, March.
    83. Narayan, Paresh Kumar & Narayan, Seema & Phan, Dinh Hoang Bach, 2022. "Terrorism and international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    84. Brownlees, Christian & Hans, Christina & Nualart, Eulalia, 2021. "Bank credit risk networks: Evidence from the Eurozone," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 585-599.
    85. Chiah, Mardy & Hu, Xiaolu & Zhong, Angel, 2022. "Photo sentiment and stock returns around the world," Finance Research Letters, Elsevier, vol. 46(PB).
    86. Humayun Kabir, M. & Shakur, Shamim, 2018. "Regime-dependent herding behavior in Asian and Latin American stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 60-78.
    87. Köstlmeier, Siegfried, 2024. "Pricing and mispricing of accounting fundamentals: Global evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 71-87.
    88. Campisi, Giovanni & Muzzioli, Silvia & De Baets, Bernard, 2024. "A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices," International Journal of Forecasting, Elsevier, vol. 40(3), pages 869-880.
    89. Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
    90. Charles, Amelie & Darne, Olivier & Kim, Jae, 2016. "Stock Return Predictability: Evaluation based on Prediction Intervals," MPRA Paper 70143, University Library of Munich, Germany.
    91. Du, Ding & Hu, Ou, 2015. "The world market risk premium and U.S. macroeconomic announcements," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 75-97.
    92. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "International Tail Risk and World Fear," Hannover Economic Papers (HEP) dp-620, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    93. Biao Guo & Qian Han & Jufang Liang & Doojin Ryu & Jinyoung Yu, 2020. "Sovereign Credit Spread Spillovers in Asia," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    94. Bahram Adrangi & Arjun Chatrath & Madhuparna Kolay & Kambiz Raffiee, 2021. "Dynamic Responses of Standard and Poor’s Regional Bank Index to the U.S. Fear Index, VIX," JRFM, MDPI, vol. 14(3), pages 1-18, March.
    95. Guo, Li & Sang, Bo & Tu, Jun & Wang, Yu, 2024. "Cross-cryptocurrency return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
    96. Xiaozhen Jing & Dezhong Xu & Bin Li & Tarlok Singh, 2024. "Does the U.S. extreme indicator matter in stock markets? International evidence," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-27, December.
    97. Wu, Shue-Jen & Lee, Wei-Ming, 2015. "Predicting severe simultaneous bear stock markets using macroeconomic variables as leading indicators," Finance Research Letters, Elsevier, vol. 13(C), pages 196-204.
    98. Zhu, Fangfei & Luo, Xingguo & Jin, Xuejun, 2019. "Predicting the volatility of the iShares China Large-Cap ETF: What is the role of the SSE 50 ETF?," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    99. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    100. Chen, Min & Zhu, Zhaobo & Han, Peiwen & Chen, Bo & Liu, Jia, 2022. "Economic policy uncertainty and analyst behaviours: Evidence from the United Kingdom," International Review of Financial Analysis, Elsevier, vol. 79(C).
    101. Dodd, Olga & Frijns, Bart & Indriawan, Ivan & Pascual, Roberto, 2023. "US cross-listing and domestic high-frequency trading: Evidence from Canadian stocks," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 301-320.
    102. Andersen, Torben G. & Todorov, Viktor & Ubukata, Masato, 2021. "Tail risk and return predictability for the Japanese equity market," Journal of Econometrics, Elsevier, vol. 222(1), pages 344-363.
    103. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," Working Papers hal-04141877, HAL.
    104. Park, Jin Suk & Newaz, Mohammad Khaleq, 2021. "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, vol. 50(C).
    105. Ying Jiang & Neil Kellard & Xiaoquan Liu, 2020. "Night trading and market quality: Evidence from Chinese and US precious metal futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1486-1507, October.
    106. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
    107. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    108. Tse, Yiuman, 2015. "Do industries lead stock markets? A reexamination," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 195-203.
    109. Christina Christou & Rangan Gupta & Fredj Jawadi, 2017. "Does Inequality Help in Forecasting Equity Premium in a Panel of G7 Countries?," Working Papers 201720, University of Pretoria, Department of Economics.
    110. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
    111. Bui, Dien Giau & Kong, De-Rong & Lin, Chih-Yung & Lin, Tse-Chun, 2023. "Momentum in machine learning: Evidence from the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    112. Kim, Hyun-Seok & Min, Hong-Ghi & McDonald, Judith A., 2016. "Returns, correlations, and volatilities in equity markets: Evidence from six OECD countries during the US financial crisis," Economic Modelling, Elsevier, vol. 59(C), pages 9-22.
    113. Ahn, Yongkil, 2022. "The anatomy of the disposition effect: Which factors are most important?," Finance Research Letters, Elsevier, vol. 44(C).
    114. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    115. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," EconomiX Working Papers 2019-8, University of Paris Nanterre, EconomiX.
    116. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    117. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    118. Ben Sita, Bernard & Abdallah, Wissam, 2014. "Volatility links between the home and the host market for U.K. dual-listed stocks on U.S. markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 183-199.
    119. Erik Hjalmarsson & Tamas Kiss, 2022. "Long‐run predictability tests are even worse than you thought," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1334-1355, November.
    120. Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019. "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, vol. 29(C), pages 315-322.
    121. José Ignacio López-Gaviria, 2019. "Colombia’s stock market predictability," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 91, pages 117-150, Julio - D.
    122. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    123. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
    124. Wang, Zijun & Qian, Yan & Wang, Shiwen, 2018. "Dynamic trading volume and stock return relation: Does it hold out of sample?," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 195-210.
    125. Jacobs, Heiko & Müller, Sebastian, 2020. "Anomalies across the globe: Once public, no longer existent?," Journal of Financial Economics, Elsevier, vol. 135(1), pages 213-230.
    126. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    127. Aslanidis, Nektarios & Hartigan, Luke, 2021. "Is the assumption of constant factor loadings too strong in practice?," Economic Modelling, Elsevier, vol. 98(C), pages 100-108.
    128. Zaremba, Adam & Kizys, Renatas & Raza, Muhammad Wajid, 2020. "The long-run reversal in the long run: Insights from two centuries of international equity returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 177-199.
    129. Celina Löwen & Bilal Kchouri & Thorsten Lehnert, 2021. "Is this time really different? Flight-to-safety and the COVID-19 crisis," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-17, May.
    130. Feng Ma & M. I. M. Wahab & Julien Chevallier & Ziyang Li, 2023. "A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 60-75, January.
    131. Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
    132. James Yae & Yang Luo, 2023. "Robust monitoring machine: a machine learning solution for out-of-sample R $$^2$$ 2 -hacking in return predictability monitoring," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    133. Junyu Zhang & Xinfeng Ruan & Jin E. Zhang, 2023. "Risk‐neutral moments and return predictability: International evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1086-1111, August.
    134. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Westerlund, Joakim, 2016. "Are Islamic stock returns predictable? A global perspective," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 210-223.
    135. Marie-Hélène Gagnon & Gabriel Power & Dominique Toupin, 2018. "Forecasting International Index Returns using Option-implied Variables," Cahiers de recherche 1807, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    136. Massimo Guidolin & Erwin Hansen & Gabriel Cabrera, 2023. "Time-Varying Risk Aversion and International Stock Returns," BAFFI CAREFIN Working Papers 23203, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    137. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    138. Hollstein, Fabian & Wese Simen, Chardin, 2020. "Variance risk: A bird’s eye view," Journal of Econometrics, Elsevier, vol. 215(2), pages 517-535.
    139. Montone, Maurizio, 2022. "Does the U.S. president affect the stock market?," Journal of Financial Markets, Elsevier, vol. 61(C).
    140. Ben Jacobsen & Ben R. Marshall & Nuttawat Visaltanachoti, 2019. "Stock Market Predictability and Industrial Metal Returns," Management Science, INFORMS, vol. 65(7), pages 3026-3042, July.
    141. Wu, Lan & Xu, Weiju & Huang, Dengshi & Li, Pan, 2022. "Does the volatility spillover effect matter in oil price volatility predictability? Evidence from high-frequency data," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 299-306.
    142. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    143. Nuno Silva, 2013. "Equity Premia Predictability in the EuroZone," GEMF Working Papers 2013-22, GEMF, Faculty of Economics, University of Coimbra.
    144. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    145. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    146. Dierkes, Maik & Hollstein, Fabian & Prokopczuk, Marcel & Würsig, Christoph Matthias, 2024. "Measuring tail risk," Journal of Econometrics, Elsevier, vol. 241(2).
    147. Xin Wang & Haofei Zhang, 2023. "The cross‐predictability of industry returns in international financial markets," International Review of Finance, International Review of Finance Ltd., vol. 23(4), pages 859-885, December.
    148. Fernandez-Perez, Adrian & Indriawan, Ivan & Tse, Yiuman & Xu, Yahua, 2023. "Cross-asset time-series momentum: Crude oil volatility and global stock markets," Journal of Banking & Finance, Elsevier, vol. 154(C).
    149. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2017. "Time series momentum and moving average trading rules," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 405-421, March.
    150. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    151. Oguzhan Cepni & Rangan Gupta & Qiang Ji, 2021. "Sentiment Regimes and Reaction of Stock Markets to Conventional and Unconventional Monetary Policies: Evidence from OECD Countries," Working Papers 202126, University of Pretoria, Department of Economics.
    152. Boyao Wu & Difang Huang & Muzi Chen, 2023. "Estimating contagion mechanism in global equity market with time‐zone effect," Financial Management, Financial Management Association International, vol. 52(3), pages 543-572, September.
    153. Shu‐Lien Chang & Hsiu‐Chuan Lee & Donald Lien, 2022. "The global latent factor and international index futures returns predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 514-538, April.
    154. Ji, Qiang & Liu, Bing-Yue & Cunado, Juncal & Gupta, Rangan, 2020. "Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    155. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    156. Su, Zhi & Fang, Tong & Yin, Libo, 2019. "Understanding stock market volatility: What is the role of U.S. uncertainty?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 582-590.
    157. Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.
    158. Chen, Ding & Guo, Biao & Zhou, Guofu, 2023. "Firm fundamentals and the cross-section of implied volatility shapes," Journal of Financial Markets, Elsevier, vol. 63(C).
    159. Abdullah Alqahtani, 2019. "Does U.S. Equity market uncertainty and implied stock market volatility affect the GCC stock markets?," Economics Bulletin, AccessEcon, vol. 39(4), pages 2631-2638.
    160. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    161. Cakici, Nusret & Zaremba, Adam, 2023. "Misery on Main Street, victory on Wall Street: Economic discomfort and the cross-section of global stock returns," Journal of Banking & Finance, Elsevier, vol. 149(C).
    162. Yanying Zhang & Yiuman Tse & Gaiyan Zhang, 2022. "Return predictability between industries and the stock market in China," Pacific Economic Review, Wiley Blackwell, vol. 27(2), pages 194-220, May.
    163. Clark, Ephraim & Lahiani, Amine & Mefteh-Wali, Salma, 2023. "Cryptocurrency return predictability: What is the role of the environment?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    164. Bagnara, Matteo, 2024. "The economic value of cross-predictability: A performance-based measure," SAFE Working Paper Series 424, Leibniz Institute for Financial Research SAFE.
    165. Chiang, Thomas C., 2022. "The effects of economic uncertainty, geopolitical risk and pandemic upheaval on gold prices," Resources Policy, Elsevier, vol. 76(C).
    166. Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
    167. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    168. Boyao Wu & Difang Huang & Muzi Chen, 2024. "Estimating Contagion Mechanism in Global Equity Market with Time-Zone Effect," Papers 2404.04335, arXiv.org.
    169. Yan, Cheng & Wang, Xichen, 2018. "The non-persistent relationship between foreign equity flows and emerging stock market returns across quantiles," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 38-54.
    170. Wen, Danyan & Wang, Gang-Jin & Ma, Chaoqun & Wang, Yudong, 2019. "Risk spillovers between oil and stock markets: A VAR for VaR analysis," Energy Economics, Elsevier, vol. 80(C), pages 524-535.
    171. Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
    172. Yi-Chieh Wen & Bin Li, 2020. "Lagged country returns and international stock return predictability during business cycle recession periods," Applied Economics, Taylor & Francis Journals, vol. 52(46), pages 5005-5019, October.
    173. Pan, Shuiyang & Long, Suwan(Cheng) & Wang, Yiming & Xie, Ying, 2023. "Nonlinear asset pricing in Chinese stock market: A deep learning approach," International Review of Financial Analysis, Elsevier, vol. 87(C).
    174. Mehmet Sahiner, 2024. "Volatility Spillovers and Contagion During Major Crises: An Early Warning Approach Based on a Deep Learning Model," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2435-2499, June.
    175. Gu, Chen & Kurov, Alexander, 2020. "Informational role of social media: Evidence from Twitter sentiment," Journal of Banking & Finance, Elsevier, vol. 121(C).
    176. Dong, Xiyong & Yoon, Seong-Min, 2019. "What global economic factors drive emerging Asian stock market returns? Evidence from a dynamic model averaging approach," Economic Modelling, Elsevier, vol. 77(C), pages 204-215.
    177. Qian Han & Jufang Liang & Boqiang Wu, 2016. "Cross Economic Determinants of Implied Volatility Smile Dynamics: Three Major European Currency Options," European Financial Management, European Financial Management Association, vol. 22(5), pages 817-852, November.
    178. Giovanni Calice & Ming Zeng, 2021. "The term structure of sovereign credit default swap and the cross‐section of exchange rate predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 445-458, January.
    179. Mitroussi, Kyriaki & Arghyrou, Michael G., 2016. "Institutional performance and ship registration," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 90-106.
    180. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    181. Zhenzhen Fan & Juan M. Londono & Xiao Xiao, 2019. "US Equity Tail Risk and Currency Risk Premia," International Finance Discussion Papers 1253, Board of Governors of the Federal Reserve System (U.S.).
    182. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    183. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
    184. Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
    185. Christian Walkshäusl & Florian Weißofner & Ulrich Wessels, 2019. "Separating momentum from reversal in international stock markets," Journal of Asset Management, Palgrave Macmillan, vol. 20(2), pages 111-123, March.
    186. Licheng Sun & Liang Meng & Mohammad Najand, 2017. "The Role of U.S. Market on International Risk-Return Tradeoff Relations," The Financial Review, Eastern Finance Association, vol. 52(3), pages 499-526, August.
    187. Londono, Juan M. & Zhou, Hao, 2017. "Variance risk premiums and the forward premium puzzle," Journal of Financial Economics, Elsevier, vol. 124(2), pages 415-440.
    188. Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
    189. Sarwar, Ghulam, 2014. "U.S. stock market uncertainty and cross-market European stock returns," Journal of Multinational Financial Management, Elsevier, vol. 28(C), pages 1-14.
    190. Biao Guo & Qian Han & Hai Lin, 2018. "Are there gains from using information over the surface of implied volatilities?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 645-672, June.
    191. Miwa, Kotaro, 2023. "Divergent opinions on social media," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 182-196.
    192. Irena Vodenska & Alexander P. Becker & Di Zhou & Dror Y. Kenett & H. Eugene Stanley & Shlomo Havlin, 2016. "Community Analysis of Global Financial Markets," Risks, MDPI, vol. 4(2), pages 1-15, May.
    193. Ahn, Jungkyu & Ahn, Yongkil, 2023. "What drives the TIPS–Treasury bond mispricing?," Journal of Empirical Finance, Elsevier, vol. 74(C).
    194. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    195. Ellington, Michael & Stamatogiannis, Michalis P. & Zheng, Yawen, 2022. "A study of cross-industry return predictability in the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    196. Stefan Fiesel & Marliese Uhrig-Homburg, 2016. "Illiquidity Transmission in a Three-Country Framework: A Conditional Approach," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 17(3), pages 261-284, December.
    197. Fu Qiao & Yan Yan, 2020. "How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19," Papers 2007.07487, arXiv.org.
    198. Shafiullah, Muhammad & Senthilkumar, Arunachalam & Lucey, Brian M. & Naeem, Muhammad Abubakr, 2024. "Deciphering asymmetric spillovers in US industries: Insights from higher-order moments," Research in International Business and Finance, Elsevier, vol. 70(PA).
    199. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2016. "Intraday return predictability, portfolio maximisation, and hedging," Emerging Markets Review, Elsevier, vol. 28(C), pages 105-116.
    200. Meng, Bo & Vijh, Anand M., 2021. "Stock merger activity and industry performance," Journal of Banking & Finance, Elsevier, vol. 129(C).
    201. Yiuman Tse, 2018. "Return predictability and contrarian profits of international index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(7), pages 788-803, July.
    202. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Narayan, Seema, 2018. "Technology-investing countries and stock return predictability," Emerging Markets Review, Elsevier, vol. 36(C), pages 159-179.
    203. Zareei, Abalfazl, 2019. "Network origins of portfolio risk," Journal of Banking & Finance, Elsevier, vol. 109(C).
    204. Wen Chen & Mozaffar Khan & Leonid Kogan & George Serafeim, 2021. "Cross‐firm return predictability and accounting quality," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 70-101, January.
    205. DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).
    206. Kang, Yong Joo & Park, Dojoon & Eom, Young Ho, 2024. "Global contagion of US COVID-19 panic news," Emerging Markets Review, Elsevier, vol. 59(C).
    207. Maxwell King & Xibin Zhang & Muhammad Akram, 2019. "Hypothesis Testing Based on a Vector of Statistics," Monash Econometrics and Business Statistics Working Papers 30/19, Monash University, Department of Econometrics and Business Statistics.
    208. Fan, Zhenzhen & Londono, Juan M. & Xiao, Xiao, 2022. "Equity tail risk and currency risk premiums," Journal of Financial Economics, Elsevier, vol. 143(1), pages 484-503.
    209. Saffet Akdag & Ömer İskenderoglu & Andrew Adewale Alola, 2020. "The volatility spillover effects among risk appetite indexes: insight from the VIX and the rise," Letters in Spatial and Resource Sciences, Springer, vol. 13(1), pages 49-65, April.
    210. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    211. Victoria Atanasov & Stig V. Møller & Richard Priestley, 2020. "Consumption Fluctuations and Expected Returns," Journal of Finance, American Finance Association, vol. 75(3), pages 1677-1713, June.
    212. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    213. Dodd, Olga & Frijns, Bart, 2018. "NYSE closure and global equity trading: The case of cross-listed stocks," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 138-150.
    214. Chiah, Mardy & Zhong, Angel, 2021. "Tuesday Blues and the day-of-the-week effect in stock returns," Journal of Banking & Finance, Elsevier, vol. 133(C).
    215. Nguyen, Dat Thanh & Phan, Dinh Hoang Bach & Anglingkusumo, Reza & Sasongko, Aryo, 2021. "US government shutdowns and Indonesian stock market," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    216. Bekiros, Stelios & Jlassi, Mouna & Naoui, Kamel & Uddin, Gazi Salah, 2017. "The asymmetric relationship between returns and implied volatility: Evidence from global stock markets," Journal of Financial Stability, Elsevier, vol. 30(C), pages 156-174.
    217. Jonathan Iworiso & Spyridon Vrontos, 2020. "On the directional predictability of equity premium using machine learning techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 449-469, April.
    218. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    219. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    220. Marshall, Ben R. & Nguyen, Hung T. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2021. "Country governance and international equity returns," Journal of Banking & Finance, Elsevier, vol. 122(C).
    221. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    222. Libo Yin & Jing Nie & Liyan Han, 2020. "Intermediary asset pricing in commodity futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1711-1730, November.
    223. Arseny Gorbenko & Marcin Kacperczyk, 2023. "Short Interest and Aggregate Stock Returns: International Evidence," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(4), pages 691-733.
    224. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    225. Hiroyuki Kawakatsu, 2022. "Local projection variance impulse response," Empirical Economics, Springer, vol. 62(3), pages 1219-1244, March.
    226. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    227. Ahn, Yongkil & Tsai, Shih-Chuan, 2021. "What factors are associated with stock price jumps in high frequency?," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    228. Muhammad Abubakr Naeem & Saqib Farid & Fiza Qureshi & Farhad Taghizadeh‐Hesary, 2023. "Global factors and the transmission between United States and emerging stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3488-3510, October.
    229. Hasselgren, Anton & Peltomäki, Jarkko & Graham, Michael, 2020. "Speculator activity and the cross-asset predictability of FX returns," International Review of Financial Analysis, Elsevier, vol. 72(C).
    230. Tissaoui, Kais & Azibi, Jamel, 2019. "International implied volatility risk indexes and Saudi stock return-volatility predictabilities," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 65-84.
    231. Ilias Tsiakas & Jiahan Li & Haibin Zhang, 2020. "Equity Premium Prediction and the State of the Economy," Working Paper series 20-16, Rimini Centre for Economic Analysis.
    232. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    233. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    234. Jiang, Danling, 2013. "The second moment matters! Cross-sectional dispersion of firm valuations and expected returns," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3974-3992.
    235. Zaremba, Adam & Szyszka, Adam & Karathanasopoulos, Andreas & Mikutowski, Mateusz, 2021. "Herding for profits: Market breadth and the cross-section of global equity returns," Economic Modelling, Elsevier, vol. 97(C), pages 348-364.
    236. David G. McMillan, 2016. "Stock return predictability and market integration: The role of global and local information," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1178363-117, December.
    237. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
    238. Hai Lin & Daniel Quill & Henk Berkman, 2016. "Information diffusion and the predictability of New Zealand stock market returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 749-785, September.
    239. Zhu, Xiaoneng & Zhu, Jie, 2013. "Predicting stock returns: A regime-switching combination approach and economic links," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4120-4133.
    240. Cheng, Hang & Shi, Yongdong, 2020. "Forecasting China's stock market variance," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    241. Westerlund, Joakim & Thuraisamy, Kannan, 2016. "Panel multi-predictor test procedures with an application to emerging market sovereign risk," Emerging Markets Review, Elsevier, vol. 28(C), pages 44-60.
    242. Nazemi, Abdolreza & Fabozzi, Frank J., 2018. "Macroeconomic variable selection for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 14-25.
    243. Elie Bouri & Rangan Gupta & Seyedmehdi Hosseini & Chi Keung Marco Lau, 2017. "Does Global Fear Predict Fear in BRICS Stock Markets? Evidence from a Bayesian Graphical VAR Model," Working Papers 201704, University of Pretoria, Department of Economics.
    244. Bahram Adrangi & Arjun Chatrath & Joseph Macri & Kambiz Raffiee, 2019. "Dynamic Responses of Major Equity Markets to the US Fear Index," JRFM, MDPI, vol. 12(4), pages 1-23, September.
    245. Guo, Xu & Lin, Hai & Wu, Chunchi & Zhou, Guofu, 2022. "Predictive information in corporate bond yields," Journal of Financial Markets, Elsevier, vol. 59(PB).
    246. Yang Bai, 2022. "150 Years of Return Predictability Around the World: A Holistic View," Papers 2209.00121, arXiv.org.
    247. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    248. Maurer, Tim D. & Nitschka, Thomas, 2023. "Stock market evidence on the international transmission channels of US monetary policy surprises," Journal of International Money and Finance, Elsevier, vol. 136(C).
    249. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
    250. Baur, Dirk G. & Löffler, Gunter, 2015. "Predicting the equity premium with the demand for gold coins and bars," Finance Research Letters, Elsevier, vol. 13(C), pages 172-178.
    251. Nusret Cakici & Christian Fieberg & Daniel Metko & Adam Zaremba, 2024. "Do Anomalies Really Predict Market Returns? New Data and New Evidence," Review of Finance, European Finance Association, vol. 28(1), pages 1-44.
    252. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    253. Wen, Yi-Chieh & Lin, Philip T. & Li, Bin & Roca, Eduardo, 2015. "Stock return predictability in South Africa: The role of major developed markets," Finance Research Letters, Elsevier, vol. 15(C), pages 257-265.
    254. Thomas C. Chiang & Yuanqing Zhang, 2018. "An Empirical Investigation of Risk-Return Relations in Chinese Equity Markets: Evidence from Aggregate and Sectoral Data," IJFS, MDPI, vol. 6(2), pages 1-22, March.
    255. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    256. Hai Lin & Pengfei Liu & Cheng Zhang, 2023. "The trend premium around the world: Evidence from the stock market," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 317-358, June.
    257. Martin Ademmer & Wolfram Horn & Josefine Quast, 2022. "Stock market dynamics and the relative importance of domestic, foreign, and common shocks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3911-3923, October.
    258. Ai He & Guofu Zhou, 2023. "Diagnostics for asset pricing models," Financial Management, Financial Management Association International, vol. 52(4), pages 617-642, December.
    259. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    260. Guettler, Andre & Hable, Patrick & Launhardt, Patrick & Miebs, Felix, 2023. "Aggregate insider trading in the S&P 500 and the predictability of international equity premia," Finance Research Letters, Elsevier, vol. 54(C).
    261. Liu, Na & Gao, Fumin, 2022. "The world uncertainty index and GDP growth rate," Finance Research Letters, Elsevier, vol. 49(C).
    262. Jia, Yuecheng & Wu, Yangru & Yan, Shu & Liu, Yuzheng, 2023. "A seesaw effect in the cryptocurrency market: Understanding the return cross predictability of cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 74(C).
    263. Jiahan Li & Ilias Tsiakas & Wei Wang, 2015. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
    264. Bravo, Francisco, 2016. "Forward-looking disclosure and corporate reputation as mechanisms to reduce stock return volatility," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 122-131.
    265. Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
    266. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
    267. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    268. Haykir, Ozkan & Yagli, Ibrahim & Aktekin Gok, Emine Dilara & Budak, Hilal, 2022. "Oil price explosivity and stock return: Do sector and firm size matter?," Resources Policy, Elsevier, vol. 78(C).
    269. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    270. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
    271. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    272. Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
    273. Andreas Gruener & Christian Finke, 2018. "Lead-Lag Relationships in International Stock Markets Revisited: Are They Exploitable?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(1), pages 8-30, January.
    274. Xu, Yahua & Xiao, Jun & Zhang, Liguo, 2020. "Global predictive power of the upside and downside variances of the U.S. equity market," Economic Modelling, Elsevier, vol. 93(C), pages 605-619.
    275. Irena Vodenska & Hideaki Aoyama & Yoshi Fujiwara & Hiroshi Iyetomi & Yuta Arai, 2016. "Interdependencies and Causalities in Coupled Financial Networks," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-32, March.
    276. Zhou, Dong-hai & Liu, Xiao-xing, 2023. "Do world stock markets “jump” together? A measure of high-frequency volatility risk spillover networks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    277. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    278. Li, Zeming & Sakkas, Athanasios & Urquhart, Andrew, 2022. "Intraday time series momentum: Global evidence and links to market characteristics," Journal of Financial Markets, Elsevier, vol. 57(C).
    279. Sakemoto, Ryuta, 2021. "Economic Evaluation of Cryptocurrency Investment," MPRA Paper 108283, University Library of Munich, Germany.
    280. Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
    281. Rama Cont & Mihai Cucuringu & Chao Zhang, 2021. "Cross-Impact of Order Flow Imbalance in Equity Markets," Papers 2112.13213, arXiv.org, revised Jun 2023.
    282. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    283. Wang, Jiqian & Ma, Feng & Wang, Tianyang & Wu, Lan, 2023. "International stock volatility predictability: New evidence from uncertainties," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    284. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    285. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.
    286. Rubia, Antonio & Sanchis-Marco, Lidia & Serrano, Pedro, 2016. "Market frictions and the pricing of sovereign credit default swaps," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 223-252.
    287. Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).
    288. Ahn, Jungkyu & Ahn, Yongkil, 2023. "Clogged pipes in the repo market," Finance Research Letters, Elsevier, vol. 57(C).
    289. Neng‐Fang Tseng & Ying‐Chao Hung & Junji Nakano, 2024. "Granger causality tests based on reduced variable information," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(3), pages 444-462, May.
    290. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 96-114.
    291. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2022. "Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    292. Balli, Faruk & Hasan, Mudassar & Ozer-Balli, Hatice & Gregory-Allen, Russell, 2021. "Why do U.S. uncertainties drive stock market spillovers? International evidence," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 288-301.
    293. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2017. "Does Financial News Predict Stock Returns? New Evidence from Islamic and Non-Islamic Stocks," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 24-45.
    294. Lu, Helen & Jacobsen, Ben, 2016. "Cross-asset return predictability: Carry trades, stocks and commodities," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 62-87.
    295. Nicholas Apergis & Rangan Gupta, 2016. "Can Weather Conditions in New York Predict South African Stock Returns?," Working Papers 201634, University of Pretoria, Department of Economics.

  11. Zhou, Guofu & Zhu, Yingzi, 2012. "Volatility Trading: What Is the Role of the Long-Run Volatility Component?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(2), pages 273-307, April.

    Cited by:

    1. Moreira, Alan & Muir, Tyler, 2019. "Should Long-Term Investors Time Volatility?," Journal of Financial Economics, Elsevier, vol. 131(3), pages 507-527.
    2. Chen, Xingjiang & Ruan, Xinfeng & Zhang, Wenjun, 2021. "Dynamic portfolio choice and information trading with recursive utility," Economic Modelling, Elsevier, vol. 98(C), pages 154-167.
    3. Song, Zhaogang & Xiu, Dacheng, 2016. "A tale of two option markets: Pricing kernels and volatility risk," Journal of Econometrics, Elsevier, vol. 190(1), pages 176-196.
    4. Marcos Escobar & Sebastian Ferrando & Alexey Rubtsov, 2017. "Optimal investment under multi-factor stochastic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 241-260, February.
    5. Wang, Qi & Wang, Zerong, 2020. "VIX valuation and its futures pricing through a generalized affine realized volatility model with hidden components and jump," Journal of Banking & Finance, Elsevier, vol. 116(C).
    6. Olesya V. Grishchenko & Zhaogang Song & Hao Zhou, 2015. "Term Structure of Interest Rates with Short-run and Long-run Risks," Finance and Economics Discussion Series 2015-95, Board of Governors of the Federal Reserve System (U.S.).
    7. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    8. Ian Dew-Becker & Stefano Giglio & Anh Le & Marius Rodriguez, 2015. "The Price of Variance Risk," NBER Working Papers 21182, National Bureau of Economic Research, Inc.
    9. Victor Troster & José Penalva & Abderrahim Taamouti & Dominik Wied, 2021. "Cointegration, information transmission, and the lead‐lag effect between industry portfolios and the stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1291-1309, November.
    10. Warren Bailey & Lin Zheng & Yinggang Zhou, 2012. "What Makes the VIX Tick?," Working Papers 222012, Hong Kong Institute for Monetary Research.
    11. Rytchkov, Oleg, 2016. "Time-Varying Margin Requirements and Optimal Portfolio Choice," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(2), pages 655-683, April.

  12. Raymond Kan & Guofu Zhou, 2012. "Tests of Mean-Variance Spanning," Annals of Economics and Finance, Society for AEF, vol. 13(1), pages 139-187, May.
    See citations under working paper version above.
  13. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    3. Thomas Trier Bjerring & Omri Ross & Alex Weissensteiner, 2017. "Feature selection for portfolio optimization," Annals of Operations Research, Springer, vol. 256(1), pages 21-40, September.
    4. Fletcher, Jonathan, 2011. "Do optimal diversification strategies outperform the 1/N strategy in U.K. stock returns?," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 375-385.
    5. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    6. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    7. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    8. Bertrand Candelon & Christophe Hurlin & Sessi Tokpavi, 2012. "Sampling Error and Double Shrinkage Estimation of Minimum Variance Portfolios," Post-Print hal-01385835, HAL.
    9. Platanakis, Emmanouil & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Horses for courses: Mean-variance for asset allocation and 1/N for stock selection," European Journal of Operational Research, Elsevier, vol. 288(1), pages 302-317.
    10. Francisco Fernández-Navarro & Luisa Martínez-Nieto & Mariano Carbonero-Ruz & Teresa Montero-Romero, 2021. "Mean Squared Variance Portfolio: A Mixed-Integer Linear Programming Formulation," Mathematics, MDPI, vol. 9(3), pages 1-13, January.
    11. Andrea Rigamonti, 2024. "Can machine learning make technical analysis work?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(3), pages 399-412, September.
    12. Chavez-Bedoya, Luis & Rosales, Francisco, 2021. "Reduction of estimation risk in optimal portfolio choice using redundant constraints," International Review of Financial Analysis, Elsevier, vol. 78(C).
    13. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2021. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Reprints LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
    14. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    15. Jonathan Fletcher, 2011. "An Examination of Dynamic Trading Stategies in UK and US Stock Returns," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1290-1310, November.
    16. Jonathan Fletcher, 2018. "An Examination of the Benefits of Factor Investing in U.K. Stock Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(4), pages 154-170, April.
    17. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    18. Matthias Horn & Andreas Oehler, 2020. "Automated portfolio rebalancing: Automatic erosion of investment performance?," Journal of Asset Management, Palgrave Macmillan, vol. 21(6), pages 489-505, October.
    19. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    20. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Harmful Diversification: Evidence from Alternative Investments," ICMA Centre Discussion Papers in Finance icma-dp2017-09, Henley Business School, University of Reading.
    21. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    22. Huang, Zhenzhen & Wei, Pengyu & Weng, Chengguo, 2024. "Tail mean-variance portfolio selection with estimation risk," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 218-234.
    23. Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2020. "An optimization–diversification approach to portfolio selection," Journal of Global Optimization, Springer, vol. 76(2), pages 245-265, February.
    24. Erik Hintz & Marius Hofert & Christiane Lemieux, 2020. "Grouped Normal Variance Mixtures," Risks, MDPI, vol. 8(4), pages 1-26, October.
    25. A. Burak Paç & Mustafa Ç. Pınar, 2018. "On robust portfolio and naïve diversification: mixing ambiguous and unambiguous assets," Annals of Operations Research, Springer, vol. 266(1), pages 223-253, July.
    26. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2022. "Sparsity and stability for minimum-variance portfolios," Risk Management, Palgrave Macmillan, vol. 24(3), pages 214-235, September.
    27. Chavez-Bedoya, Luis & Rosales, Francisco, 2022. "Orthogonal portfolios to assess estimation risk," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 906-937.
    28. Kristiaan Kerstens & Paolo Mazza & Tiantian Ren & Ignace Van de Woestyne, 2021. "Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy," Working Papers 2021-EQM-03, IESEG School of Management.
    29. Bertrand Maillet & Sessi Tokpavi & Benoit Vaucher, 2013. "Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach," EconomiX Working Papers 2013-28, University of Paris Nanterre, EconomiX.
    30. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean-Variance Efficient Large Portfolios : A Simple Machine Learning Heuristic Technique based on the Two-Fund Separation Theorem," Post-Print hal-04514343, HAL.
    31. Yao, Haixiang & Huang, Jinbo & Li, Yong & Humphrey, Jacquelyn E., 2021. "A general approach to smooth and convex portfolio optimization using lower partial moments," Journal of Banking & Finance, Elsevier, vol. 129(C).
    32. Kourtis, Apostolos & Dotsis, George & Markellos, Raphael N., 2012. "Parameter uncertainty in portfolio selection: Shrinking the inverse covariance matrix," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2522-2531.
    33. Steven E. Pav, 2014. "Bounds on Portfolio Quality," Papers 1409.5936, arXiv.org.
    34. Behr, Patrick & Guettler, Andre & Miebs, Felix, 2013. "On portfolio optimization: Imposing the right constraints," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1232-1242.
    35. Yen, Yu-Min & Yen, Tso-Jung, 2014. "Solving norm constrained portfolio optimization via coordinate-wise descent algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 737-759.
    36. Giovanni Bonaccolto, 2021. "Quantile– based portfolios: post– model– selection estimation with alternative specifications," Computational Management Science, Springer, vol. 18(3), pages 355-383, July.
    37. Bonaccolto, Giovanni & Caporin, Massimiliano & Maillet, Bertrand B., 2022. "Dynamic large financial networks via conditional expected shortfalls," European Journal of Operational Research, Elsevier, vol. 298(1), pages 322-336.
    38. Ni, Xuanming & Zheng, Tiantian & Zhao, Huimin & Zhu, Shushang, 2023. "High-dimensional portfolio optimization based on tree-structured factor model," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    39. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the benefits of active stock selection strategies for diversified investors," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 342-354.
    40. Billio, Monica & Caporin, Massimiliano & Costola, Michele, 2015. "Backward/forward optimal combination of performance measures for equity screening," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 63-83.
    41. Yonghe Lu & Yanrong Yang & Terry Zhang, 2024. "Double Descent in Portfolio Optimization: Dance between Theoretical Sharpe Ratio and Estimation Accuracy," Papers 2411.18830, arXiv.org.
    42. Ren, Tiantian & Kerstens, Kristiaan & Kumar, Saurav, 2024. "Risk-aversion versus risk-loving preferences in nonparametric frontier-based fund ratings: A buy-and-hold backtesting strategy," European Journal of Operational Research, Elsevier, vol. 319(1), pages 332-344.
    43. Chulwoo Han, 2020. "How much should portfolios shrink?," Financial Management, Financial Management Association International, vol. 49(3), pages 707-740, September.
    44. Auer, Benjamin R. & Schuhmacher, Frank, 2016. "Do socially (ir)responsible investments pay? New evidence from international ESG data," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 51-62.
    45. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    46. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.
    47. Huang, Hung-Hsi & Lin, Shin-Hung & Wang, Ching-Ping & Chiu, Chia-Yung, 2014. "Adjusting MV-efficient portfolio frontier bias for skewed and non-mesokurtic returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 59-83.
    48. Raymond Kan & Xiaolu Wang & Guofu Zhou, 2022. "Optimal Portfolio Choice with Estimation Risk: No Risk-Free Asset Case," Management Science, INFORMS, vol. 68(3), pages 2047-2068, March.
    49. Jonathan Fletcher, 2022. "Exploring the diversification benefits of US international equity closed-end funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 297-320, September.
    50. Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
    51. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    52. Dragon Yongjun Tang, 2014. "Potential losses from incorporating return predictability into portfolio allocation," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 35-45, February.
    53. Hjalmarsson, Erik & Manchev, Petar, 2012. "Characteristic-based mean-variance portfolio choice," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1392-1401.
    54. Bertrand Maillet & Sessi Tokpavi & Benoit Vaucher, 2013. "Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach," Working Papers hal-04141193, HAL.
    55. Raymond Kan & Xiaolu Wang, 2024. "Optimal Portfolio Choice with Unknown Benchmark Efficiency," Management Science, INFORMS, vol. 70(9), pages 6117-6138, September.
    56. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    57. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2020. "Can Volatility Solve the Naive Portfolio Puzzle?," Papers 2005.03204, arXiv.org, revised Feb 2022.
    58. Forbes, William & Hudson, Robert & Skerratt, Len & Soufian, Mona, 2015. "Which heuristics can aid financial-decision-making?," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 199-210.
    59. Kim Oosterlinck & Ariane Reyns & Ariane Szafarz, 2022. "Gold, Bitcoin, and Portfolio Diversification: Lessons from the Ukrainian War," Working Papers CEB 22-008, ULB -- Universite Libre de Bruxelles.
    60. Mörstedt, Torsten & Lutz, Bernhard & Neumann, Dirk, 2024. "Cross validation based transfer learning for cross-sectional non-linear shrinkage: A data-driven approach in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(2), pages 670-685.
    61. Fletcher, Jonathan, 2018. "An empirical examination of the diversification benefits of U.K. international equity closed-end funds," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 23-34.
    62. Füss, Roland & Miebs, Felix & Trübenbach, Fabian, 2014. "A jackknife-type estimator for portfolio revision," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 14-28.
    63. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    64. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    65. Chen, Xiangyu & Tongurai, Jittima, 2021. "Cross-commodity hedging for illiquid futures: Evidence from China's base metal futures market," Global Finance Journal, Elsevier, vol. 49(C).
    66. Behr, Patrick & Guettler, Andre & Truebenbach, Fabian, 2012. "Using industry momentum to improve portfolio performance," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1414-1423.
    67. Hubert Dichtl & Wolfgang Drobetz & Viktoria‐Sophie Wendt, 2021. "How to build a factor portfolio: Does the allocation strategy matter?," European Financial Management, European Financial Management Association, vol. 27(1), pages 20-58, January.
    68. Stivers, Adam, 2018. "Equity premium predictions with many predictors: A risk-based explanation of the size and value factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 126-140.
    69. Sangwon Suh, 2016. "A Combination Rule for Portfolio Selection with Transaction Costs," International Review of Finance, International Review of Finance Ltd., vol. 16(3), pages 393-420, September.
    70. Allen, D. & Lizieri, C. & Satchell, S., 2012. "Mean-Variance versus 1/N: What if we can forecast? (Updated 22nd December 2013)," Cambridge Working Papers in Economics 1244, Faculty of Economics, University of Cambridge.
    71. Jaspersen, Johannes G., 2022. "Convex combinations in judgment aggregation," European Journal of Operational Research, Elsevier, vol. 299(2), pages 780-794.
    72. Giovanni Bonaccolto, 2019. "Critical Decisions for Asset Allocation via Penalized Quantile Regression," Papers 1908.04697, arXiv.org.
    73. Tu, Xueyong & Li, Bin, 2024. "Robust portfolio selection with smart return prediction," Economic Modelling, Elsevier, vol. 135(C).
    74. M. Ryan Haley, 2017. "K-fold cross validation performance comparisons of six naive portfolio selection rules: how naive can you be and still have successful out-of-sample portfolio performance?," Annals of Finance, Springer, vol. 13(3), pages 341-353, August.
    75. Xia Han & Liyuan Lin & Ruodu Wang, 2022. "Diversification quotients: Quantifying diversification via risk measures," Papers 2206.13679, arXiv.org, revised Jul 2024.
    76. Sang Il Lee, 2020. "Deeply Equal-Weighted Subset Portfolios," Papers 2006.14402, arXiv.org.
    77. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2020. "Company classification using machine learning," Papers 2004.01496, arXiv.org, revised May 2020.
    78. Fletcher, Jonathan, 2021. "International equity U.S. mutual funds and diversification benefits," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 246-257.
    79. Taras Bodnar & Ostap Okhrin & Nestor Parolya, 2016. "Optimal Shrinkage Estimator for High-Dimensional Mean Vector," Papers 1610.09292, arXiv.org, revised Jul 2018.
    80. Kircher, Felix & Rösch, Daniel, 2021. "A shrinkage approach for Sharpe ratio optimal portfolios with estimation risks," Journal of Banking & Finance, Elsevier, vol. 133(C).
    81. Hwang, Inchang & Xu, Simon & In, Francis, 2018. "Naive versus optimal diversification: Tail risk and performance," European Journal of Operational Research, Elsevier, vol. 265(1), pages 372-388.
    82. Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2020. "Does sophistication of the weighting scheme enhance the performance of long-short commodity portfolios?," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 164-180.
    83. Jonathan Berrisch & Florian Ziel, 2021. "CRPS Learning," Papers 2102.00968, arXiv.org, revised Nov 2021.
    84. Peter Christoffersen & Vihang Errunza & Kris Jacobs & Hugues Langlois, 2012. "Is the Potential for International Diversi?cation Disappearing? A Dynamic Copula Approach," CREATES Research Papers 2012-48, Department of Economics and Business Economics, Aarhus University.
    85. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Sparsity and Stability for Minimum-Variance Portfolios," Papers 1910.11840, arXiv.org.
    86. Nicholas Taylor, 2014. "The Economic Value of Volatility Forecasts: A Conditional Approach," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 433-478.
    87. Cheng Yan & Ji Yan, 2021. "Optimal and naive diversification in an emerging market: Evidence from China's A‐shares market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3740-3758, July.
    88. Kourtis, Apostolos, 2014. "On the distribution and estimation of trading costs," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 104-117.
    89. Olson, Eric & Vivian, Andrew & Wohar, Mark E., 2019. "What is a better cross-hedge for energy: Equities or other commodities?," Global Finance Journal, Elsevier, vol. 42(C).
    90. Kamal, Javed Bin, 2012. "Optimal portfolio selection in ex ante stock price bubble and furthermore bubble burst scenario from Dhaka stock exchange with relevance to sharpe’s single index model," MPRA Paper 60610, University Library of Munich, Germany.
    91. Jelena Vidovic, 2013. "Investigation Of Stock Illiquidity On Central And South East European Markets In Naã Ve Portfolio Framework," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 22(2), pages 537-550, december.
    92. Carlos Castro-Iragorri, 2019. "Does the market model provide a good counterfactual for event studies in finance?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 71-91, March.
    93. Schanbacher Peter, 2015. "Averaging Across Asset Allocation Models," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(1), pages 61-81, February.
    94. Johannes Bock, 2018. "An updated review of (sub-)optimal diversification models," Papers 1811.08255, arXiv.org.
    95. Li, Xiaoyue & Uysal, A. Sinem & Mulvey, John M., 2022. "Multi-period portfolio optimization using model predictive control with mean-variance and risk parity frameworks," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1158-1176.
    96. Yudong Wang & Chongfeng Wu & Li Yang, 2015. "Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy?," Management Science, INFORMS, vol. 61(12), pages 2870-2889, December.
    97. Moorman, Theodore, 2014. "An empirical investigation of methods to reduce transaction costs," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 230-246.
    98. Yu Li & Yuhan Wu & Shuhua Zhang, 2024. "The mean-variance portfolio selection based on the average and current profitability of the risky asset," Papers 2408.07969, arXiv.org.
    99. Caner, Mehmet & Medeiros, Marcelo & Vasconcelos, Gabriel F.R., 2023. "Sharpe Ratio analysis in high dimensions: Residual-based nodewise regression in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 393-417.
    100. Immo Stadtmüller & Benjamin R. Auer & Frank Schuhmacher, 2024. "Core-satellite investing with commodity futures momentum," Journal of Asset Management, Palgrave Macmillan, vol. 25(3), pages 261-287, May.
    101. Wang, Chou-Wen & Liu, Kai & Li, Bin & Tan, Ken Seng, 2022. "Portfolio optimization under multivariate affine generalized hyperbolic distributions," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 49-66.
    102. Fabozzi, Frank J. & Huang, Dashan & Jiang, Fuwei & Wang, Jiexun, 2024. "What difference do new factor models make in portfolio allocation?," Journal of International Money and Finance, Elsevier, vol. 140(C).
    103. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Should Portfolio Model Inputs Be Estimated Using One or Two Economic Regimes?," ICMA Centre Discussion Papers in Finance icma-dp2017-07, Henley Business School, University of Reading.
    104. Andrew Paskaramoorthy & Tim Gebbie & Terence van Zyl, 2021. "The efficient frontiers of mean-variance portfolio rules under distribution misspecification," Papers 2106.10491, arXiv.org, revised Jul 2021.
    105. Niu, Xiaojian & Niu, Xiaoli & Wu, Kexing, 2021. "Implicit government guarantees and the externality of portfolio diversification: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    106. Chiarawongse, Anant & Kiatsupaibul, Seksan & Tirapat, Sunti & Roy, Benjamin Van, 2012. "Portfolio selection with qualitative input," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 489-496.
    107. Michael Senescall & Rand Kwong Yew Low, 2024. "Quantitative Portfolio Management: Review and Outlook," Mathematics, MDPI, vol. 12(18), pages 1-25, September.
    108. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    109. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    110. Lassance, Nathan & Vanderveken, Rodolphe & Vrins, Frédéric, 2022. "On the optimal combination of naive and mean-variance portfolio strategies," LIDAM Discussion Papers LFIN 2022006, Université catholique de Louvain, Louvain Finance (LFIN).
    111. Pflug, Georg Ch. & Pichler, Alois & Wozabal, David, 2012. "The 1/N investment strategy is optimal under high model ambiguity," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 410-417.
    112. Matthias M. M. Buehlmaier & Kit Pong Wong, 2020. "Should investors join the index revolution? Evidence from around the world," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 192-218, May.
    113. Jonathan Fletcher & Elizabeth Littlejohn & Andrew Marshall, 2023. "Exploring the performance of US international bond mutual funds," The Financial Review, Eastern Finance Association, vol. 58(4), pages 765-782, November.
    114. Olivier Ledoit & Michael Wolf, 2014. "Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks," ECON - Working Papers 137, Department of Economics - University of Zurich, revised Feb 2017.
    115. Anja Vinzelberg & Benjamin R. Auer, 2022. "Unprofitability of food market investments," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2887-2910, October.
    116. Yijian Chuan & Chaoyi Zhao & Zhenrui He & Lan Wu, 2021. "The Success of AdaBoost and Its Application in Portfolio Management," Papers 2103.12345, arXiv.org.
    117. Erindi Allaj, 2020. "The Black–Litterman model and views from a reverse optimization procedure: an out-of-sample performance evaluation," Computational Management Science, Springer, vol. 17(3), pages 465-492, October.
    118. Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2016. "When Micro Prudence Increases Macro Risk: The Destabilizing Effects of Financial Innovation, Leverage, and Diversification," Operations Research, INFORMS, vol. 64(5), pages 1073-1088, October.
    119. Hongseon Kim & Soonbong Lee & Seung Bum Soh & Seongmoon Kim, 2022. "Improving portfolio investment performance with distance‐based portfolio‐combining algorithms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(4), pages 941-959, December.
    120. Levy, Haim & Levy, Moshe, 2014. "The benefits of differential variance-based constraints in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 372-381.
    121. Joo, Young C. & Park, Sung Y., 2021. "Optimal portfolio selection using a simple double-shrinkage selection rule," Finance Research Letters, Elsevier, vol. 43(C).
    122. Olivier Brandouy & Kristiaan Kerstens & Ignace Van De Woestyne, 2015. "Frontier-based vs. traditional mutual fund ratings: A first backtesting analysis," Post-Print hal-01533555, HAL.
    123. Glennon, Dennis & Kiefer, Hua & Mayock, Tom, 2018. "Measurement error in residential property valuation: An application of forecast combination," Journal of Housing Economics, Elsevier, vol. 41(C), pages 1-29.
    124. Donatien Tafin Djoko & Yves Till�, 2015. "Selection of balanced portfolios to track the main properties of a large market," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 359-370, February.
    125. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    126. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2015. "Equally Weighted vs. Long†Run Optimal Portfolios," European Financial Management, European Financial Management Association, vol. 21(4), pages 742-789, September.
    127. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
    128. Enrico G. De Giorgi & Ola Mahmoud, 2016. "Naive Diversification Preferences and their Representation," Papers 1611.01285, arXiv.org, revised Nov 2016.
    129. Han, Chulwoo, 2020. "A nonparametric approach to portfolio shrinkage," Journal of Banking & Finance, Elsevier, vol. 120(C).
    130. Yan, Cheng & Zhang, Huazhu, 2017. "Mean-variance versus naïve diversification: The role of mispricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 61-81.
    131. Fletcher, Jonathan, 2018. "Betas V characteristics: Do stock characteristics enhance the investment opportunity set in U.K. stock returns?," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 114-129.
    132. Chakrabarti, Deepayan, 2021. "Parameter-free robust optimization for the maximum-Sharpe portfolio problem," European Journal of Operational Research, Elsevier, vol. 293(1), pages 388-399.
    133. Berrisch, Jonathan & Ziel, Florian, 2023. "CRPS learning," Journal of Econometrics, Elsevier, vol. 237(2).
    134. Branger, Nicole & Lučivjanská, Katarína & Weissensteiner, Alex, 2019. "Optimal granularity for portfolio choice," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 125-146.
    135. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    136. Giovanni Bonaccolto & Sandra Paterlini, 2020. "Developing new portfolio strategies by aggregation," Annals of Operations Research, Springer, vol. 292(2), pages 933-971, September.
    137. Víctor M. Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, "undated". "Portfolios in the Ibex 35 index: Alternative methods to the traditional framework, a comparative with the naive diversification in a pre- and post- crisis context," Documentos de Trabajo del ICAE 2015-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Jun 2015.
    138. Zhu, Bo & Zhang, Tianlun, 2021. "Long-term wealth growth portfolio allocation under parameter uncertainty: A non-conservative robust approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    139. Miguel, Victor de & Nogales, Francisco J., 2013. "Parameter uncertainty in multiperiod portfolio optimization with transaction costs," DES - Working Papers. Statistics and Econometrics. WS ws132119, Universidad Carlos III de Madrid. Departamento de Estadística.
    140. Max Heide & Benjamin R. Auer & Frank Schuhmacher, 2025. "Optimal Versus Naive Diversification in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(1), pages 3-22, January.
    141. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J., 2013. "Size matters: Optimal calibration of shrinkage estimators for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3018-3034.
    142. Zakamulin, Valeriy, 2017. "Superiority of optimized portfolios to naive diversification: Fact or fiction?," Finance Research Letters, Elsevier, vol. 22(C), pages 122-128.
    143. Prince C Nwakanma & Monday Aberiate Gbanador, 2014. "Talmud and Markowitz Diversification Strategies: Evidence from the Nigerian Stock Market," Accounting and Finance Research, Sciedu Press, vol. 3(2), pages 145-145, May.
    144. Kourtis, Apostolos, 2016. "The Sharpe ratio of estimated efficient portfolios," Finance Research Letters, Elsevier, vol. 17(C), pages 72-78.
    145. Víctor Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2017. "“Resolution of optimization problems and construction of efficient portfolios: An application to the Euro Stoxx 50 index"," IREA Working Papers 201702, University of Barcelona, Research Institute of Applied Economics, revised Feb 2017.
    146. Miralles-Marcelo, José Luis & Miralles-Quirós, María del Mar & Miralles-Quirós, José Luis, 2015. "Improving international diversification benefits for US investors," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 64-76.
    147. Zhou, Zhongbao & Xiao, Helu & Jin, Qianying & Liu, Wenbin, 2018. "DEA frontier improvement and portfolio rebalancing: An application of China mutual funds on considering sustainability information disclosure," European Journal of Operational Research, Elsevier, vol. 269(1), pages 111-131.
    148. Kazak, Ekaterina & Pohlmeier, Winfried, 2019. "Testing out-of-sample portfolio performance," International Journal of Forecasting, Elsevier, vol. 35(2), pages 540-554.
    149. Jiang, Chonghui & Du, Jiangze & An, Yunbi & Zhang, Jinqing, 2021. "Factor tracking: A new smart beta strategy that outperforms naïve diversification," Economic Modelling, Elsevier, vol. 96(C), pages 396-408.

  14. Gormley, Todd & Liu, Hong & Zhou, Guofu, 2010. "Limited participation and consumption-saving puzzles: A simple explanation and the role of insurance," Journal of Financial Economics, Elsevier, vol. 96(2), pages 331-344, May.

    Cited by:

    1. Lee, Hangsuck & Ryu, Doojin & Son, Jihoon, 2022. "Insurance-adjusted valuation, decision making, and capital return," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Niu, Geng & Wang, Qi & Li, Han & Zhou, Yang, 2020. "Number of brothers, risk sharing, and stock market participation," Journal of Banking & Finance, Elsevier, vol. 113(C).
    3. Agrawal, Ashwini K. & Matsa, David A., 2013. "Labor unemployment risk and corporate financing decisions," LSE Research Online Documents on Economics 69608, London School of Economics and Political Science, LSE Library.
    4. Da Ke, 2021. "Who Wears the Pants? Gender Identity Norms and Intrahousehold Financial Decision‐Making," Journal of Finance, American Finance Association, vol. 76(3), pages 1389-1425, June.
    5. Rui Li & Jing Wu & Shuo Zhang & Siqing Zhang & Yuanyang Wu, 2023. "Social Endowment Insurance and Inequality of the Household Portfolio Choice: The Moderating Effect of Financial Literacy," SAGE Open, , vol. 13(1), pages 21582440231, February.
    6. Devos, Erik & Rahman, Shofiqur, 2018. "Labor unemployment insurance and firm cash holdings," Journal of Corporate Finance, Elsevier, vol. 49(C), pages 15-31.
    7. Caroline Flammer & Jiao Luo, 2017. "Corporate social responsibility as an employee governance tool: Evidence from a quasi-experiment," Strategic Management Journal, Wiley Blackwell, vol. 38(2), pages 163-183, February.
    8. Jang, Bong-Gyu & Park, Seyoung & Rhee, Yuna, 2013. "Optimal retirement with unemployment risks," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3585-3604.
    9. Dal Borgo, Mariela, 2021. "Do bankruptcy protection levels affect households' demand for stocks?," CAGE Online Working Paper Series 564, Competitive Advantage in the Global Economy (CAGE).
    10. Jang, Bong-Gyu & Park, Seyoung & Zhao, Huainan, 2020. "Optimal retirement with borrowing constraints and forced unemployment risk," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 25-39.
    11. Xin, Xinyi & Zhang, Anquan & Liu, Lu, 2024. "Study on the influence of Internet finance on urban household savings rate: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 45-61.
    12. Ya-Fang Cheng & Eugene Burgos Mutuc & Fu-Sheng Tsai & Kun-Hwa Lu & Chien-Ho Lin, 2018. "Social Capital and Stock Market Participation via Technologies: The Role of Households’ Risk Attitude and Cognitive Ability," Sustainability, MDPI, vol. 10(6), pages 1-14, June.
    13. Yinan Yang & Qian Wang, 2018. "Insurance Inclusion, Time Preference And Stock Investment Of The Chinese Households," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(01), pages 27-44, March.
    14. Francesco D'Acunto & Marcel Prokopczuk & Michael Weber & Michael Weber, 2017. "Historical Antisemitism, Ethnic Specialization, and Financial Development," CESifo Working Paper Series 6643, CESifo.
    15. Sinha, Rajesh Kumar, 2021. "Macro disagreement and analyst forecast properties," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(1).
    16. Carpio, Ronaldo & Guo, Meixin & Liu, Yuan & Pyun, Ju Hyun, 2021. "Wealth heterogeneity, information acquisition and equity home bias: Evidence from U.S. household surveys of consumer finance," Journal of Banking & Finance, Elsevier, vol. 126(C).
    17. Bae, Se Yung & Jeon, Junkee & Koo, Hyeng Keun & Park, Kyunghyun, 2020. "Social insurance for the elderly," Economic Modelling, Elsevier, vol. 91(C), pages 274-299.
    18. Ulya Tsolmon & Dan Ariely, 2022. "Health insurance benefits as a labor market friction: Evidence from a quasi‐experiment," Strategic Management Journal, Wiley Blackwell, vol. 43(8), pages 1556-1574, August.
    19. Qiuyun Wang & Lu Liu, 2022. "Pandemic or panic? A firm-level study on the psychological and industrial impacts of COVID-19 on the Chinese stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.
    20. Cancheng Hong & Di He & Ting Ren, 2023. "The Impact of Commercial Medical Insurance Participation on Household Debt," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    21. Li, Jingrong & Mi, Xinyu & Zhang, Chenlei & Qin, Yanran, 2024. "Social pension insurance and household risky asset investment: Evidence from China," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 219-233.
    22. Joanne W. Hsu & David A. Matsa & Brian T. Melzer, 2014. "Positive Externalities of Social Insurance: Unemployment Insurance and Consumer Credit," NBER Working Papers 20353, National Bureau of Economic Research, Inc.
    23. Peter Chinloy & Daniel Winkler, 2012. "Contracts, Individual Revenue and Performance," Journal of Labor Research, Springer, vol. 33(4), pages 545-562, December.
    24. Alain Bensoussan & Bong-Gyu Jang & Seyoung Park, 2016. "Unemployment Risks and Optimal Retirement in an Incomplete Market," Operations Research, INFORMS, vol. 64(4), pages 1015-1032, August.
    25. He, Zekai & Shi, Xiuzhen & Lu, Xiaomeng & Li, Feng, 2019. "Home equity and household portfolio choice: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 149-164.
    26. Devos, Erik & Rahman, Shofiqur, 2023. "Does labor unemployment insurance affect corporate tax aggressiveness?," International Review of Financial Analysis, Elsevier, vol. 90(C).
    27. Yulin Liu & Min Zhang, 2020. "Is household registration system responsible for the limited participation of stock market in China?," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 13(3), pages 332-350, July.
    28. Gill, Balbinder Singh, 2023. "Health uninsurance premium and mortgage interest rates," International Review of Financial Analysis, Elsevier, vol. 87(C).
    29. Shen, Yi, 2022. "Labor unemployment insurance and bank loans," Journal of Corporate Finance, Elsevier, vol. 76(C).
    30. Liu, Xueying & Zhao, Zhong, 2024. "Does Social Pension Insurance Increase the Efficiency of Household Financial Portfolios?," IZA Discussion Papers 17492, Institute of Labor Economics (IZA).

  15. Zhou, Guofu, 2010. "How much stock return predictability can we expect from an asset pricing model?," Economics Letters, Elsevier, vol. 108(2), pages 184-186, August.

    Cited by:

    1. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    2. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    3. Baetje, Fabian & Menkhoff, Lukas, 2013. "Macro determinants of U.S. stock market risk premia in bull and bear markets," Hannover Economic Papers (HEP) dp-520, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Baoqing Gan, 2020. "Does Social Media Sentiment Trump News?," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2020, January-A.
    5. Cunha, Ronan & Pereira, Pedro L. Valls, 2015. "Automatic model selection for forecasting Brazilian stock returns," Textos para discussão 398, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    6. Davide Pettenuzzo & Allan Timmermann & Rossen Valkanov, 2013. "Forecasting Stock Returns under Economic Constraints," Working Papers 57, Brandeis University, Department of Economics and International Business School.
    7. Potì, Valerio & Levich, Richard & Conlon, Thomas, 2020. "Predictability and pricing efficiency in forward and spot, developed and emerging currency markets," Journal of International Money and Finance, Elsevier, vol. 107(C).
    8. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    9. Tom Engsted & Stig V. Møller & Magnus Sander, 2013. "Bond return predictability in expansions and recessions," CREATES Research Papers 2013-13, Department of Economics and Business Economics, Aarhus University.
    10. Becker, Janis & Leschinski, Christian, 2018. "Directional Predictability of Daily Stock Returns," Hannover Economic Papers (HEP) dp-624, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    11. David E. Rapach & Matthew C. Ringgenberg & Guofu Zhou, 2016. "Short interest and aggregate stock returns," CEMA Working Papers 716, China Economics and Management Academy, Central University of Finance and Economics.
    12. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    13. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    14. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    15. Brennan, M.J. & Taylor, Alex P., 2023. "Expected returns and risk in the stock market," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 276-300.
    16. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    17. Hjalmarsson, Erik, 2018. "Maximal predictability under long-term mean reversion," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 269-282.
    18. Potì, Valerio, 2018. "A new tight and general bound on return predictability," Economics Letters, Elsevier, vol. 162(C), pages 140-145.
    19. Hai Lin & Daniel Quill & Henk Berkman, 2016. "Information diffusion and the predictability of New Zealand stock market returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 749-785, September.
    20. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    21. Fletcher, Jonathan & Basu, Devraj, 2016. "An examination of the benefits of dynamic trading strategies in U.K. closed-end funds," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 109-118.

  16. Frank Fabozzi & Dashan Huang & Guofu Zhou, 2010. "Robust portfolios: contributions from operations research and finance," Annals of Operations Research, Springer, vol. 176(1), pages 191-220, April.

    Cited by:

    1. Nathan Lassance & Frédéric Vrins, 2019. "Minimum Rényi entropy portfolios," LIDAM Reprints CORE 3062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Güray Kara & Ayşe Özmen & Gerhard-Wilhelm Weber, 2019. "Stability advances in robust portfolio optimization under parallelepiped uncertainty," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 241-261, March.
    3. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    4. Jang Ho Kim & Woo Chang Kim & Do-Gyun Kwon & Frank J. Fabozzi, 2018. "Robust equity portfolio performance," Annals of Operations Research, Springer, vol. 266(1), pages 293-312, July.
    5. Aharon Ben-Tal & Dick den Hertog & Anja De Waegenaere & Bertrand Melenberg & Gijs Rennen, 2013. "Robust Solutions of Optimization Problems Affected by Uncertain Probabilities," Management Science, INFORMS, vol. 59(2), pages 341-357, April.
    6. Martin Branda & Max Bucher & Michal Červinka & Alexandra Schwartz, 2018. "Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization," Computational Optimization and Applications, Springer, vol. 70(2), pages 503-530, June.
    7. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    8. K. Liagkouras & K. Metaxiotis, 2018. "A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem," Annals of Operations Research, Springer, vol. 267(1), pages 281-319, August.
    9. Klerkx, Rik & Pelsser, Antoon, 2022. "Narrative-based robust stochastic optimization," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 266-277.
    10. Jang Ho Kim & Yongjae Lee & Woo Chang Kim & Frank J. Fabozzi, 2022. "Goal-based investing based on multi-stage robust portfolio optimization," Annals of Operations Research, Springer, vol. 313(2), pages 1141-1158, June.
    11. A. Burak Paç & Mustafa Ç. Pınar, 2018. "On robust portfolio and naïve diversification: mixing ambiguous and unambiguous assets," Annals of Operations Research, Springer, vol. 266(1), pages 223-253, July.
    12. Antonios Georgantas & Michalis Doumpos & Constantin Zopounidis, 2024. "Robust optimization approaches for portfolio selection: a comparative analysis," Annals of Operations Research, Springer, vol. 339(3), pages 1205-1221, August.
    13. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    14. William Lefebvre & Grégoire Loeper & Huyên Pham, 2020. "Mean-Variance Portfolio Selection with Tracking Error Penalization," Mathematics, MDPI, vol. 8(11), pages 1-23, November.
    15. Hongxin Zhao & Yilun Jiang & Yizhou Yang, 2023. "Robust and Sparse Portfolio: Optimization Models and Algorithms," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
    16. Bertrand Maillet & Sessi Tokpavi & Benoit Vaucher, 2013. "Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach," EconomiX Working Papers 2013-28, University of Paris Nanterre, EconomiX.
    17. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    18. Noureddine Kouaissah & Sergio Ortobelli Lozza & Ikram Jebabli, 2022. "Portfolio Selection Using Multivariate Semiparametric Estimators and a Copula PCA-Based Approach," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 833-859, October.
    19. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2018. "Recent advancements in robust optimization for investment management," Annals of Operations Research, Springer, vol. 266(1), pages 183-198, July.
    20. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.
    21. Wei Liu & Li Yang & Bo Yu, 2022. "Kernel density estimation based distributionally robust mean-CVaR portfolio optimization," Journal of Global Optimization, Springer, vol. 84(4), pages 1053-1077, December.
    22. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    23. Kaiqiang An & Guiyu Zhao & Jinjun Li & Jingsong Tian & Lihua Wang & Liang Xian & Chen Chen, 2023. "Best-Case Scenario Robust Portfolio: Evidence from China Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(2), pages 297-322, June.
    24. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    25. Mazin Al Janabi, 2013. "Optimal and coherent economic-capital structures: evidence from long and short-sales trading positions under illiquid market perspectives," Annals of Operations Research, Springer, vol. 205(1), pages 109-139, May.
    26. Ran Ji & Miguel A. Lejeune & Srinivas Y. Prasad, 2017. "Properties, formulations, and algorithms for portfolio optimization using Mean-Gini criteria," Annals of Operations Research, Springer, vol. 248(1), pages 305-343, January.
    27. Panos Xidonas & Mike Tsionas & Constantin Zopounidis, 2018. "On mutual funds-of-ETFs asset allocation with rebalancing: sample covariance versus EWMA and GARCH," Post-Print hal-02880066, HAL.
    28. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.
    29. Lotfi, Somayyeh & Zenios, Stavros A., 2018. "Robust VaR and CVaR optimization under joint ambiguity in distributions, means, and covariances," European Journal of Operational Research, Elsevier, vol. 269(2), pages 556-576.
    30. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    31. Jingnan Chen & Gengling Dai & Ning Zhang, 2020. "An application of sparse-group lasso regularization to equity portfolio optimization and sector selection," Annals of Operations Research, Springer, vol. 284(1), pages 243-262, January.
    32. Immanuel M. Bomze & Michael Kahr & Markus Leitner, 2021. "Trust Your Data or Not—StQP Remains StQP: Community Detection via Robust Standard Quadratic Optimization," Mathematics of Operations Research, INFORMS, vol. 46(1), pages 301-316, February.
    33. Dragon Yongjun Tang, 2014. "Potential losses from incorporating return predictability into portfolio allocation," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 35-45, February.
    34. Juan F. Monge & Mercedes Landete & Jos'e L. Ruiz, 2016. "Sharpe portfolio using a cross-efficiency evaluation," Papers 1610.00937, arXiv.org, revised Oct 2016.
    35. Dilip B. Madan, 2016. "Conic Portfolio Theory," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-42, May.
    36. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    37. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh, 2019. "An enhanced procedure for managing blood supply chain under disruptions and uncertainties," Annals of Operations Research, Springer, vol. 283(1), pages 1413-1462, December.
    38. Marchioni, Andrea & Magni, Carlo Alberto, 2018. "Investment decisions and sensitivity analysis: NPV-consistency of rates of return," European Journal of Operational Research, Elsevier, vol. 268(1), pages 361-372.
    39. Selim Mankaï, 2014. "Data-Driven Robust Optimization with Application to Portfolio Management," Working Papers 2014-104, Department of Research, Ipag Business School.
    40. N. Meade & J. E. Beasley & C. J. Adcock, 2019. "Quantitative portfolio selection: using density forecasting to find consistent portfolios," Papers 1908.08442, arXiv.org, revised Jun 2020.
    41. Aida Toma & Samuela Leoni-Aubin, 2015. "Robust Portfolio Optimization Using Pseudodistances," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-26, October.
    42. Selim Mankaï & Khaled Guesmi, 2014. "Robust Portfolio Protection: A Scenarios-Based Approach," EconomiX Working Papers 2014-35, University of Paris Nanterre, EconomiX.
    43. Sangwon Suh, 2016. "A Combination Rule for Portfolio Selection with Transaction Costs," International Review of Finance, International Review of Finance Ltd., vol. 16(3), pages 393-420, September.
    44. Balter, Anne G. & Pelsser, Antoon, 2020. "Pricing and hedging in incomplete markets with model uncertainty," European Journal of Operational Research, Elsevier, vol. 282(3), pages 911-925.
    45. Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.
    46. Lassance, Nathan & Vrins, Frédéric, 2019. "Robust portfolio selection using sparse estimation of comoment tensors," LIDAM Discussion Papers LFIN 2019007, Université catholique de Louvain, Louvain Finance (LFIN).
    47. Balter, Anne G. & Mahayni, Antje & Schweizer, Nikolaus, 2021. "Time-consistency of optimal investment under smooth ambiguity," European Journal of Operational Research, Elsevier, vol. 293(2), pages 643-657.
    48. Milford, James & Henrion, Max & Hunter, Chad & Newes, Emily & Hughes, Caroline & Baldwin, Samuel F., 2022. "Energy sector portfolio analysis with uncertainty," Applied Energy, Elsevier, vol. 306(PA).
    49. Xidonas, Panos & Hassapis, Christis & Soulis, John & Samitas, Aristeidis, 2017. "Robust minimum variance portfolio optimization modelling under scenario uncertainty," Economic Modelling, Elsevier, vol. 64(C), pages 60-71.
    50. Pavel Bazovkin & Karl Mosler, 2015. "A general solution for robust linear programs with distortion risk constraints," Annals of Operations Research, Springer, vol. 229(1), pages 103-120, June.
    51. A. Georgantas, 2020. "Robust Optimization Approaches for Portfolio Selection: A Computational and Comparative Analysis," Papers 2010.13397, arXiv.org.
    52. Kim, Woo Chang & Kim, Jang Ho & Mulvey, John M. & Fabozzi, Frank J., 2015. "Focusing on the worst state for robust investing," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 19-31.
    53. Wei Liu & Li Yang & Bo Yu, 2021. "KDE distributionally robust portfolio optimization with higher moment coherent risk," Annals of Operations Research, Springer, vol. 307(1), pages 363-397, December.
    54. Ken Kobayashi & Yuichi Takano & Kazuhide Nakata, 2021. "Bilevel cutting-plane algorithm for cardinality-constrained mean-CVaR portfolio optimization," Journal of Global Optimization, Springer, vol. 81(2), pages 493-528, October.
    55. Branger, Nicole & Mahayni, Antje & Zieling, Daniel, 2015. "Robustness of stable volatility strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 134-151.
    56. William Lefebvre & Gregoire Loeper & Huy^en Pham, 2020. "Mean-variance portfolio selection with tracking error penalization," Papers 2009.08214, arXiv.org, revised Sep 2020.
    57. I-Chen Lu & Kai-Hong Tee & Baibing Li, 2019. "Asset allocation with multiple analysts’ views: a robust approach," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 215-228, May.
    58. Lotfi, Somayyeh & Zeniosn, Stravros A., 2016. "Equivalence of Robust VaR and CVaR Optimization," Working Papers 16-03, University of Pennsylvania, Wharton School, Weiss Center.
    59. Willliam Lefebvre & Gregoire Loeper & Huyên Pham, 2020. "Mean-variance portfolio selection with tracking error penalization," Working Papers hal-02941289, HAL.
    60. Andreas Thomann, 2021. "Multi-asset scenario building for trend-following trading strategies," Annals of Operations Research, Springer, vol. 299(1), pages 293-315, April.
    61. Lu Wang & Ferhana Ahmad & Gong-li Luo & Muhammad Umar & Dervis Kirikkaleli, 2022. "Portfolio optimization of financial commodities with energy futures," Annals of Operations Research, Springer, vol. 313(1), pages 401-439, June.
    62. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    63. Robert Durand & John Gould & Ross Maller, 2011. "On the performance of the minimum VaR portfolio," The European Journal of Finance, Taylor & Francis Journals, vol. 17(7), pages 553-576.
    64. Benati, S. & Conde, E., 2022. "A relative robust approach on expected returns with bounded CVaR for portfolio selection," European Journal of Operational Research, Elsevier, vol. 296(1), pages 332-352.
    65. Woo Kim & Jang Kim & So Ahn & Frank Fabozzi, 2013. "What do robust equity portfolio models really do?," Annals of Operations Research, Springer, vol. 205(1), pages 141-168, May.
    66. Hachmi Ben Ameur & Mouna Boujelbène & J. L. Prigent & Emna Triki, 2020. "Optimal Portfolio Positioning on Multiple Assets Under Ambiguity," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 21-57, June.
    67. Zhenlong Jiang & Ran Ji & Kuo-Chu Chang, 2020. "A Machine Learning Integrated Portfolio Rebalance Framework with Risk-Aversion Adjustment," JRFM, MDPI, vol. 13(7), pages 1-20, July.
    68. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    69. Tiago P. Filomena & Miguel A. Lejeune, 2014. "Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 308-329, April.
    70. Geng Deng & Tim Dulaney & Craig McCann & Olivia Wang, 2013. "Robust portfolio optimization with Value-at-Risk-adjusted Sharpe ratios," Journal of Asset Management, Palgrave Macmillan, vol. 14(5), pages 293-305, October.
    71. Ben-Tal, A. & den Hertog, D. & De Waegenaere, A.M.B. & Melenberg, B. & Rennen, G., 2011. "Robust Solutions of Optimization Problems Affected by Uncertain Probabilities," Other publications TiSEM 4d43dc51-86d9-4804-8563-9, Tilburg University, School of Economics and Management.
    72. Thorsten Poddig & Albina Unger, 2012. "On the robustness of risk-based asset allocations," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(3), pages 369-401, September.
    73. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
    74. Sergio Ortobelli & Sebastiano Vitali & Marco Cassader & Tomáš Tichý, 2018. "Portfolio selection strategy for fixed income markets with immunization on average," Annals of Operations Research, Springer, vol. 260(1), pages 395-415, January.
    75. Erindi Allaj, 2020. "The Black–Litterman model and views from a reverse optimization procedure: an out-of-sample performance evaluation," Computational Management Science, Springer, vol. 17(3), pages 465-492, October.
    76. Kim, Jang Ho & Kim, Woo Chang & Fabozzi, Frank J., 2013. "Composition of robust equity portfolios," Finance Research Letters, Elsevier, vol. 10(2), pages 72-81.
    77. Maria Scutellà & Raffaella Recchia, 2013. "Robust portfolio asset allocation and risk measures," Annals of Operations Research, Springer, vol. 204(1), pages 145-169, April.
    78. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    79. Bazovkin, Pavel & Mosler, Karl, 2011. "Stochastic linear programming with a distortion risk constraint," Discussion Papers in Econometrics and Statistics 6/11, University of Cologne, Institute of Econometrics and Statistics.
    80. Peter Nystrup & Stephen Boyd & Erik Lindström & Henrik Madsen, 2019. "Multi-period portfolio selection with drawdown control," Annals of Operations Research, Springer, vol. 282(1), pages 245-271, November.
    81. Kobayashi, Ken & Takano, Yuichi & Nakata, Kazuhide, 2023. "Cardinality-constrained distributionally robust portfolio optimization," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1173-1182.
    82. Mazin A.M. Al Janabi, 2021. "Is optimum always optimal? A revisit of the mean‐variance method under nonlinear measures of dependence and non‐normal liquidity constraints," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 387-415, April.
    83. Jun-ya Gotoh & Akiko Takeda, 2011. "On the role of norm constraints in portfolio selection," Computational Management Science, Springer, vol. 8(4), pages 323-353, November.
    84. Omid Momen & Akbar Esfahanipour & Abbas Seifi, 2020. "A robust behavioral portfolio selection: model with investor attitudes and biases," Operational Research, Springer, vol. 20(1), pages 427-446, March.
    85. Magni, Carlo Alberto & Marchioni, Andrea & Baschieri, Davide, 2023. "The Attribution Matrix and the joint use of Finite Change Sensitivity Index and Residual Income for value-based performance measurement," European Journal of Operational Research, Elsevier, vol. 306(2), pages 872-892.
    86. Ward Romeijnders & Krzysztof Postek, 2021. "Piecewise Constant Decision Rules via Branch-and-Bound Based Scenario Detection for Integer Adjustable Robust Optimization," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 390-400, January.
    87. Selim Mankai & Khaled Guesmi, 2014. "Robust Portfolio Protection: A Scenarios-Based Approach," Working Papers hal-04141326, HAL.
    88. Xidonas, Panos & Doukas, Haris & Hassapis, Christis, 2021. "Grouped data, investment committees & multicriteria portfolio selection," Journal of Business Research, Elsevier, vol. 129(C), pages 205-222.
    89. Sara Biagini & Mustafa Pinar, 2015. "The Robust Merton Problem of an Ambiguity Averse Investor," Papers 1502.02847, arXiv.org.
    90. Sergio Ortobelli & Noureddine Kouaissah & Tomáš Tichý, 2019. "On the use of conditional expectation in portfolio selection problems," Annals of Operations Research, Springer, vol. 274(1), pages 501-530, March.
    91. Kim, Woo Chang & Kim, Min Jeong & Kim, Jang Ho & Fabozzi, Frank J., 2014. "Robust portfolios that do not tilt factor exposure," European Journal of Operational Research, Elsevier, vol. 234(2), pages 411-421.
    92. Ashrafi, Hedieh & Thiele, Aurélie C., 2021. "A study of robust portfolio optimization with European options using polyhedral uncertainty sets," Operations Research Perspectives, Elsevier, vol. 8(C).
    93. Salo, Ahti & Doumpos, Michalis & Liesiö, Juuso & Zopounidis, Constantin, 2024. "Fifty years of portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(1), pages 1-18.
    94. Zhaolin Hu & Jing Cao & L. Jeff Hong, 2012. "Robust Simulation of Global Warming Policies Using the DICE Model," Management Science, INFORMS, vol. 58(12), pages 2190-2206, December.
    95. T. D. Chuong & V. Jeyakumar, 2017. "An Exact Formula for Radius of Robust Feasibility of Uncertain Linear Programs," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 203-226, April.
    96. Kim, Jang Ho & Kim, Woo Chang & Fabozzi, Frank J., 2016. "Portfolio selection with conservative short-selling," Finance Research Letters, Elsevier, vol. 18(C), pages 363-369.
    97. Xidonas, Panos & Mavrotas, George & Hassapis, Christis & Zopounidis, Constantin, 2017. "Robust multiobjective portfolio optimization: A minimax regret approach," European Journal of Operational Research, Elsevier, vol. 262(1), pages 299-305.
    98. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    99. Bazovkin, Pavel, 2014. "Geometrical framework for robust portfolio optimization," Discussion Papers in Econometrics and Statistics 01/14, University of Cologne, Institute of Econometrics and Statistics.
    100. Shujian Ma & Jilong Cai & Gang Wang & Xiangxiang Ge & Ying Teng & Hua Jiang, 2024. "Research on Decision Analysis with CVaR for Supply Chain Finance Based on Blockchain Technology," Mathematics, MDPI, vol. 12(3), pages 1-25, January.
    101. Fernandes, Betina & Street, Alexandre & Valladão, Davi & Fernandes, Cristiano, 2016. "An adaptive robust portfolio optimization model with loss constraints based on data-driven polyhedral uncertainty sets," European Journal of Operational Research, Elsevier, vol. 255(3), pages 961-970.
    102. Dupačová, Jitka & Kopa, Miloš, 2014. "Robustness of optimal portfolios under risk and stochastic dominance constraints," European Journal of Operational Research, Elsevier, vol. 234(2), pages 434-441.
    103. Annalisa Fabretti & Stefano Herzel & Mustafa C. Pinar, 2014. "Delegated Portfolio Management under Ambiguity Aversion," CEIS Research Paper 304, Tor Vergata University, CEIS, revised 06 Feb 2014.
    104. Zhilin Kang & Zhongfei Li, 2018. "An exact solution to a robust portfolio choice problem with multiple risk measures under ambiguous distribution," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(2), pages 169-195, April.
    105. Kim, Woo Chang & Kim, Jang Ho & Fabozzi, Frank J., 2014. "Deciphering robust portfolios," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 1-8.

  17. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2023. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 126151, London School of Economics and Political Science, LSE Library.
    3. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    4. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    5. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    6. Bodnar, Olha & Bodnar, Taras & Niklasson, Vilhelm, 2024. "Constructing Bayesian tangency portfolios under short-selling restrictions," Finance Research Letters, Elsevier, vol. 62(PA).
    7. D. J. Johnstone, 2021. "Accounting information, disclosure, and expected utility: Do investors really abhor uncertainty?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 3-35, January.
    8. Evan Anderson & Ai-ru (Meg) Cheng, 2022. "Portfolio Choices with Many Big Models," Management Science, INFORMS, vol. 68(1), pages 690-715, January.
    9. Carmine De Franco & Johann Nicolle & Huy^en Pham, 2018. "Bayesian learning for the Markowitz portfolio selection problem," Papers 1811.06893, arXiv.org.
    10. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    11. Fuertes, Ana-Maria & Zhao, Nan, 2023. "A Bayesian perspective on commodity style integration," Journal of Commodity Markets, Elsevier, vol. 30(C).
    12. Bauder, David & Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2020. "Bayesian inference of the multi-period optimal portfolio for an exponential utility," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    13. Carmine De Franco & Johann Nicolle & Huyên Pham, 2019. "Dealing with Drift Uncertainty: A Bayesian Learning Approach," Risks, MDPI, vol. 7(1), pages 1-18, January.
    14. Kellerer, Belinda, 2019. "Portfolio Optimization and Ambiguity Aversion," Junior Management Science (JUMS), Junior Management Science e. V., vol. 4(3), pages 305-338.
    15. Andrew Ang & Andrés Ayala & William N. Goetzmann, 2018. "Investment beliefs of endowments," European Financial Management, European Financial Management Association, vol. 24(1), pages 3-33, January.
    16. Jessica Wachter, 2010. "Asset Allocation," NBER Working Papers 16255, National Bureau of Economic Research, Inc.
    17. Chulwoo Han, 2020. "How much should portfolios shrink?," Financial Management, Financial Management Association International, vol. 49(3), pages 707-740, September.
    18. Bodnar, Taras & Mazur, Stepan & Nguyen, Hoang, 2022. "Estimation of optimal portfolio compositions for small sampleand singular covariance matrix," Working Papers 2022:15, Örebro University, School of Business.
    19. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    20. Dragon Yongjun Tang, 2014. "Potential losses from incorporating return predictability into portfolio allocation," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 35-45, February.
    21. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
    22. Massimo Guidolin & Hening Liu, 2013. "Ambiguity Aversion and Under-diversification," Working Papers 483, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    23. Scott Cederburg & Travis L Johnson & Michael S O’Doherty, 2023. "On the Economic Significance of Stock Return Predictability," Review of Finance, European Finance Association, vol. 27(2), pages 619-657.
    24. David Bauder & Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2021. "Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 221-242, February.
    25. Sangwon Suh, 2016. "A Combination Rule for Portfolio Selection with Transaction Costs," International Review of Finance, International Review of Finance Ltd., vol. 16(3), pages 393-420, September.
    26. Taras Bodnar & Vilhelm Niklasson & Erik Thors'en, 2022. "Volatility Sensitive Bayesian Estimation of Portfolio VaR and CVaR," Papers 2205.01444, arXiv.org.
    27. Carmine de Franco & Johann Nicolle & Huyên Pham, 2018. "Bayesian learning for the Markowitz portfolio selection problem," Working Papers hal-01923917, HAL.
    28. Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.
    29. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Integrated Deviance Information Criterion for Latent Variable Models," Economics and Statistics Working Papers 6-2018, Singapore Management University, School of Economics.
    30. David Bauder & Taras Bodnar & Stepan Mazur & Yarema Okhrin, 2018. "Bayesian Inference For The Tangent Portfolio," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-27, December.
    31. Taras Bodnar & Mathias Lindholm & Vilhelm Niklasson & Erik Thors'en, 2020. "Bayesian Quantile-Based Portfolio Selection," Papers 2012.01819, arXiv.org.
    32. Kontosakos, Vasileios E. & Hwang, Soosung & Kallinterakis, Vasileios & Pantelous, Athanasios A., 2024. "Long-term dynamic asset allocation under asymmetric risk preferences," European Journal of Operational Research, Elsevier, vol. 312(2), pages 765-782.
    33. Johannes Bock, 2018. "An updated review of (sub-)optimal diversification models," Papers 1811.08255, arXiv.org.
    34. Mihnea S. Andrei & Sujit K. Ghosh & Jian Zou, 2021. "Dynamic Correlation Multivariate Stochastic Volatility Black-Litterman With Latent Factors," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(2), pages 1-1, March.
    35. Carmine De Franco & Johann Nicolle & Huyên Pham, 2019. "Bayesian Learning For The Markowitz Portfolio Selection Problem," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(07), pages 1-40, November.
    36. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
    37. Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
    38. Paulo M.M. Rodrigues & Gabriel Zsurkis, 2023. "First passage times in portfolio optimization: a novel nonparametric approach," Working Papers w202309, Banco de Portugal, Economics and Research Department.
    39. Chirag Shekhar & Mark Trede, 2017. "Portfolio Optimization Using Multivariate t-Copulas with Conditionally Skewed Margins," Review of Economics & Finance, Better Advances Press, Canada, vol. 9, pages 29-41, August.
    40. Fuhrer, Adrian & Hock, Thorsten, 2019. "Uncertainty in the Black-Litterman model: A practical note," Weidener Diskussionspapiere 68, University of Applied Sciences Amberg-Weiden (OTH).
    41. Matthias M. M. Buehlmaier & Kit Pong Wong, 2020. "Should investors join the index revolution? Evidence from around the world," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 192-218, May.
    42. Chiaki Hara & Toshiki Honda, 2014. "Asset Demand and Ambiguity Aversion," KIER Working Papers 911, Kyoto University, Institute of Economic Research.
    43. Bodnar, Taras & Mazur, Stepan & Okhrin, Yarema, 2017. "Bayesian estimation of the global minimum variance portfolio," European Journal of Operational Research, Elsevier, vol. 256(1), pages 292-307.
    44. Erindi Allaj, 2013. "The Black–Litterman model: a consistent estimation of the parameter tau," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(2), pages 217-251, June.
    45. Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
    46. Ahmed Imran Hunjra & Tahar Tayachi & Rashid Mehmood & Sidra Malik & Zoya Malik, 2020. "Impact of Credit Risk on Momentum and Contrarian Strategies: Evidence from South Asian Markets," Risks, MDPI, vol. 8(2), pages 1-14, April.
    47. Han, Chulwoo, 2020. "A nonparametric approach to portfolio shrinkage," Journal of Banking & Finance, Elsevier, vol. 120(C).
    48. Khoa Dang Duong & Ngoc Thi Thanh Nguyen & Nga Thu Thi Do & Hoa Thanh Phan Le, 2024. "Limit to Arbitrage and Distress Risk Puzzle in Vietnam: Does Corporate Bankruptcy Regulation Matter?," SAGE Open, , vol. 14(2), pages 21582440241, May.
    49. Merkle, Christoph, 2017. "Financial overconfidence over time: Foresight, hindsight, and insight of investors," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 68-87.
    50. Hung, Ming-Chin & Hsia, Ping-Hung & Kuang, Xian-Ji & Lin, Shih-Kuei, 2024. "Intelligent portfolio construction via news sentiment analysis," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 605-617.
    51. Guanhao Feng & Jingyu He, 2019. "Factor Investing: A Bayesian Hierarchical Approach," Papers 1902.01015, arXiv.org, revised Sep 2020.

  18. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.

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    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    5. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    6. Markus Leippold & Hanlin Yang, 2023. "Mixed‐frequency predictive regressions with parameter learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1955-1972, December.
    7. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    8. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    9. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    10. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    11. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    12. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    13. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    14. Boriss Siliverstovs, 2016. "International Stock Return Predictability: On the Role of the United States in Bad and Good Times," KOF Working papers 16-408, KOF Swiss Economic Institute, ETH Zurich.
    15. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    16. Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
    17. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    18. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    19. Avdoulas, Christos & Bekiros, Stelios & Boubaker, Sabri, 2016. "Detecting nonlinear dependencies in eurozone peripheral equity markets: A multistep filtering approach," Economic Modelling, Elsevier, vol. 58(C), pages 580-587.
    20. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    21. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    22. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    23. Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2016. "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(3), pages 273-291.
    24. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    25. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    26. Theologos Dergiades & Panos K. Pouliasis, 2021. "Should Stock Returns Predictability be hooked on Long Horizon Regressions?," Discussion Paper Series 2021_03, Department of Economics, University of Macedonia, revised Feb 2021.
    27. Esther Eiling & Raymond Kan & Ali Sharifkhani, 2018. "Sectoral Labor Reallocation and Return Predictability," Working Papers 2018-006, Human Capital and Economic Opportunity Working Group.
    28. Chen, Junping & Xiong, Xiong & Zhu, Jie & Zhu, Xiaoneng, 2017. "Asset prices and economic fluctuations: The implications of stochastic volatility," Economic Modelling, Elsevier, vol. 64(C), pages 128-140.
    29. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    30. Su, Yuandong & Lu, Xinjie & Zeng, Qing & Huang, Dengshi, 2022. "Good air quality and stock market returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    31. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    32. Wang, Cindy S.H. & Fan, Rui & Xie, Yiqiang, 2023. "Market systemic risk, predictability and macroeconomics news," Finance Research Letters, Elsevier, vol. 56(C).
    33. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    34. Lee A. Smales, 2016. "Trading behavior in S&P 500 index futures," Review of Financial Economics, John Wiley & Sons, vol. 28(1), pages 46-55, January.
    35. Li, Xiaodan & Gong, Xue & Xing, Lu, 2024. "The impact of presidential economic approval rating on stock volatility: An industrial perspective," Finance Research Letters, Elsevier, vol. 63(C).
    36. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    37. Smith, Simon C., 2017. "Equity premium estimates from economic fundamentals under structural breaks," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 49-61.
    38. Li, Dakai & Zhang, Fan & Li, Xuezhi, 2022. "Can U.S. trade policy uncertainty help in predicting stock market excess return?," Finance Research Letters, Elsevier, vol. 49(C).
    39. Srivastava, Sasha & Lin, Hai & Premachandra, Inguruwatte M. & Roberts, Helen, 2016. "Global risk spillover and the predictability of sovereign CDS spread: International evidence," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 371-390.
    40. Zongwu Cai & Haiqiang Chen & Xiaosai Liao, 2020. "A New Robust Inference for Predictive Quantile Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202002, University of Kansas, Department of Economics, revised Feb 2020.
    41. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    42. Narayan, Paresh Kumar & Narayan, Seema & Thuraisamy, Kannan Sivananthan, 2014. "Can institutions and macroeconomic factors predict stock returns in emerging markets?," Emerging Markets Review, Elsevier, vol. 19(C), pages 77-95.
    43. Scholz, Michael & Nielsen, Jens Perch & Sperlich, Stefan, 2015. "Nonparametric prediction of stock returns based on yearly data: The long-term view," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 143-155.
    44. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    45. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
    46. Pham, Quynh Thi Thuy & Rudolf, Markus, 2021. "Gold, platinum, and industry stock returns," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 252-266.
    47. Qingxiang Han & Mengxi He & Yaojie Zhang & Muhammad Umar, 2023. "Default return spread: A powerful predictor of crude oil price returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1786-1804, November.
    48. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    49. Zhang, Lixia & Luo, Qin & Guo, Xiaozhu & Umar, Muhammad, 2022. "Medium-term and long-term volatility forecasts for EUA futures with country-specific economic policy uncertainty indices," Resources Policy, Elsevier, vol. 77(C).
    50. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2023. "Panel Data Nowcasting: The Case of Price-Earnings Ratios," Papers 2307.02673, arXiv.org.
    51. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    52. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2014. "Sticky prices or economically-linked economies: The case of forecasting the Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 95-109.
    53. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    54. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    55. Shi, Chunpei & Wei, Yu & Li, Xiafei & Liu, Yuntong, 2023. "Combination forecasts of China's oil futures returns based on multiple uncertainties and their connectedness with oil," Energy Economics, Elsevier, vol. 126(C).
    56. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    57. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    58. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    59. Yaojie Zhang & Qingxiang Han & Mengxi He, 2024. "Forecasting stock market returns with a lottery index: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1595-1606, August.
    60. Daniel Buncic, 2016. "Superforecasting: The Art and Science of Prediction. By Philip Tetlock and Dan Gardner," Risks, MDPI, vol. 4(3), pages 1-5, July.
    61. Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
    62. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    63. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    64. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
    65. Pérez-Quirós, Gabriel & Diaz, Elena, 2020. "Daily Tracker of Global Economic Activity. A Close-Up of the Covid-19 Pandemic," CEPR Discussion Papers 15451, C.E.P.R. Discussion Papers.
    66. Paresh Kumar Narayan & Seema Narayan & Siroos Khademalomoom & Dinh Hoang Bach Phan, 2018. "Do Terrorist Attacks Impact Exchange Rate Behavior? New International Evidence," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 547-561, January.
    67. Ma, Feng & Lu, Fei & Tao, Ying, 2022. "Geopolitical risk and excess stock returns predictability: New evidence from a century of data," Finance Research Letters, Elsevier, vol. 50(C).
    68. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75, Brandeis University, Department of Economics and International Business School.
    69. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    70. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    71. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    72. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    73. Lyu, Zhichong & Ma, Feng & Zhang, Jixiang, 2023. "Oil futures volatility prediction: Bagging or combination?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 457-467.
    74. Shi, Qi & Li, Bin, 2022. "Further evidence on financial information and economic activity forecasts in the United States," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    75. Kenechukwu E. Anadu & James Bohn & Lina Lu & Matthew Pritsker & Andrei Zlate, 2019. "Reach for Yield by U.S. Public Pension Funds," Finance and Economics Discussion Series 2019-048, Board of Governors of the Federal Reserve System (U.S.).
    76. Chen, Cathy Yi-Hsuan & Després, Roméo & Guo, Li & Renault, Thomas, 2019. "What makes cryptocurrencies special? Investor sentiment and return predictability during the bubble," IRTG 1792 Discussion Papers 2019-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    77. Yin, Libo & Su, Zhi & Lu, Man, 2022. "Is oil risk important for commodity-related currency returns?," Research in International Business and Finance, Elsevier, vol. 60(C).
    78. Rachidi Kotchoni & Dalibor Stevanovic, 2020. "GDP Forecast Accuracy During Recessions," Working Papers 20-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    79. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    80. Hong, Yongmiao & Lin, Hai & Wu, Chunchi, 2012. "Are corporate bond market returns predictable?," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2216-2232.
    81. Yiwen (Paul) Dou & David R. Gallagher & David Schneider & Terry S. Walter, 2012. "Out-of-sample stock return predictability in Australia," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 461-479, December.
    82. Manuela Pedio, 2021. "Option-Implied Network Measures of Tail Contagion and Stock Return Predictability," BAFFI CAREFIN Working Papers 21154, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    83. Xu, Yongan & Liang, Chao & Wang, Jianqiong, 2023. "Financial stress and returns predictability: Fresh evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    84. Yu, Deshui & Chen, Li, 2024. "Local predictability of stock returns and cash flows," Journal of Empirical Finance, Elsevier, vol. 77(C).
    85. Rangan Gupta & Yuvana Jaichand & Christian Pierdzioch & Reneé van Eyden, 2023. "Realized Stock-Market Volatility of the United States and the Presidential Approval Rating," Mathematics, MDPI, vol. 11(13), pages 1-27, July.
    86. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    87. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    88. Lu Wang & Feng Ma & Guoshan Liu, 2020. "Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 797-810, August.
    89. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Business School, revised Feb 2018.
    90. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    91. Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2013. "Can Economic Uncertainty, Financial Stress and Consumer Sentiments Predict U.S. Equity Premium?," Working Papers 201351, University of Pretoria, Department of Economics.
    92. Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
    93. Chen, Yan & Zhang, Lei & Zhang, Feipeng, 2024. "Forecasting crude oil volatility and stock volatility: New evidence from the quantile autoregressive model," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    94. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    95. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
    96. Jurdi, Doureige & Kim, Jae, 2019. "Predicting the U.S. Stock Market Return: Evidence from the Improved Augmented Regression Method," MPRA Paper 94028, University Library of Munich, Germany.
    97. Dai, Zhifeng & Zhou, Huiting & Wen, Fenghua & He, Shaoyi, 2020. "Efficient predictability of stock return volatility: The role of stock market implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    98. Narayan, Paresh Kumar & Sharma, Susan Sunila & Thuraisamy, Kannan S., 2015. "Can governance quality predict stock market returns? New global evidence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 367-380.
    99. Tzeng, Kae-Yih & Su, Yi-Kai, 2024. "Can U.S. macroeconomic indicators forecast cryptocurrency volatility?," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    100. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
    101. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    102. Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
    103. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
    104. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    105. Taylor, Mark, 2014. "Common Macro Factors and Currency Premia," CEPR Discussion Papers 10016, C.E.P.R. Discussion Papers.
    106. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    107. Hossein Rad & Rand Kwong Yew Low & Joelle Miffre & Robert Faff, 2022. "The Strategic Allocation to Style-Integrated Portfolios of Commodity Futures," Post-Print hal-03881976, HAL.
    108. Tobias Götze & Marc Gürtler & Eileen Witowski, 2020. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 428-446, September.
    109. Peter Christoffersen & Mathieu Fournier & Kris Jacobs & Mehdi Karoui, 2015. "Option-Based Estimation of the Price of Co-Skewness and Co-Kurtosis Risk," CREATES Research Papers 2015-54, Department of Economics and Business Economics, Aarhus University.
    110. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    111. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    112. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    113. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    114. Zhu, Min & Chen, Rui & Du, Ke & Wang, You-Gan, 2018. "Dividend growth and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 125-137.
    115. Massimo Guidolin & Manuela Pedio & Milena Petrova, 2019. "The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis," BAFFI CAREFIN Working Papers 19122, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    116. Stefan Nagel & Zhengyang Xu, 2022. "Dynamics of Subjective Risk Premia," NBER Working Papers 29803, National Bureau of Economic Research, Inc.
    117. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    118. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    119. Scholz, Michael & Sperlich, Stefan & Nielsen, Jens Perch, 2016. "Nonparametric long term prediction of stock returns with generated bond yields," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 82-96.
    120. Zhang, Dan & Li, Biangxiang, 2022. "What can we learn from financial stress indicator?," Finance Research Letters, Elsevier, vol. 50(C).
    121. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    122. Davide Pettenuzzo & Riccardo Sabbatucci & Allan Timmermann, 2020. "Cash Flow News and Stock Price Dynamics," Journal of Finance, American Finance Association, vol. 75(4), pages 2221-2270, August.
    123. Afees A. Salisu & Raymond Swaray & Tirimisyu F. Oloko, 2017. "A multi-factor predictive model for oil-US stock nexus with persistence, endogeneity and conditional heteroscedasticity effects," Working Papers 024, Centre for Econometric and Allied Research, University of Ibadan.
    124. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    125. Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
    126. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    127. Rohloff, Sebastian & Pierdzioch, Christian & Risse, Marian, 2014. "Fluctuations of the Real Exchange Rate, Real Interest Rates, and the Dynamics of the Price of Gold in a Small Open Economy," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100429, Verein für Socialpolitik / German Economic Association.
    128. Narayan, Paresh Kumar, 2019. "Can stale oil price news predict stock returns?," Energy Economics, Elsevier, vol. 83(C), pages 430-444.
    129. Lv, Wendai & Qi, Jipeng, 2022. "Stock market return predictability: A combination forecast perspective," International Review of Financial Analysis, Elsevier, vol. 84(C).
    130. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    131. Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
    132. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    133. Lu, Fei & Ma, Feng, 2023. "Cross-sectional uncertainty and stock market volatility: New evidence," Finance Research Letters, Elsevier, vol. 57(C).
    134. Zhikai Zhang & Yaojie Zhang & Yudong Wang & Qunwei Wang, 2024. "The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 557-584, April.
    135. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    136. Wei, Yu & Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A., 2023. "Cryptocurrency uncertainty and volatility forecasting of precious metal futures markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
    137. Nianling Wang & Lijie Zhang & Zhuo Huang & Yong Li, 2021. "Asymmetric Correlations in Predicting Portfolio Returns," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 97-120, March.
    138. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
    139. Xianfeng Hao & Yudong Wang, 2023. "Forecasting the stock risk premium: A new statistical constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1805-1822, November.
    140. Samson Adeniyi Aladejare, 2019. "Testing the Robustness of Public Spending Determinants on Public Spending Decisions in Nigeria," International Economic Journal, Taylor & Francis Journals, vol. 33(1), pages 65-87, January.
    141. Sousa, Ricardo M. & Vivian, Andrew & Wohar, Mark E., 2016. "Predicting asset returns in the BRICS: The role of macroeconomic and fundamental predictors," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 122-143.
    142. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
    143. Taylor, Nicholas, 2012. "Measuring the economic value of loan advice," Economics Letters, Elsevier, vol. 117(3), pages 615-618.
    144. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    145. Yae, James & Tian, George Zhe, 2022. "Out-of-sample forecasting of cryptocurrency returns: A comprehensive comparison of predictors and algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    146. Cao, Zhen & Han, Liyan & Wei, Xinbei & Zhang, Qunzi, 2022. "Fear in commodity return prediction," Finance Research Letters, Elsevier, vol. 46(PB).
    147. Strauss, Jack, 2013. "Does housing drive state-level job growth? Building permits and consumer expectations forecast a state’s economic activity," Journal of Urban Economics, Elsevier, vol. 73(1), pages 77-93.
    148. Haibin Xie & Shouyang Wang, 2015. "Risk-return trade-off, information diffusion, and U.S. stock market predictability," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-20, December.
    149. Erik Hillebrand & Tae-Hwy Lee & Marcelo Cunha Medeiros, 2012. "Let´s do it again: bagging equity premium predictors," Textos para discussão 604, Department of Economics PUC-Rio (Brazil).
    150. Guo, Biao & Han, Qian & Lin, Hai, 2015. "Forecasting the Term Structure of Implied Volatilities," Working Paper Series 20148, Victoria University of Wellington, School of Economics and Finance.
    151. Xianzheng Zhou & Hui Zhou & Huaigang Long, 2023. "Forecasting the equity premium: Do deep neural network models work?," Modern Finance, Modern Finance Institute, vol. 1(1), pages 1-11.
    152. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    153. Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
    154. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    155. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    156. Yu, Jize & Zhang, Li & Peng, Lijuan & Wu, Rui, 2023. "Which component of air quality index drives stock price volatility in China: a decomposition-based forecasting method," Finance Research Letters, Elsevier, vol. 51(C).
    157. Samuel YM Ze‐To, 2022. "Fundamental index aligned and excess market return predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 592-614, April.
    158. Xu, Yongan & Duong, Duy & Xu, Hualong, 2023. "Attention! Predicting crude oil prices from the perspective of extreme weather," Finance Research Letters, Elsevier, vol. 57(C).
    159. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    160. Liu, Zhichao & Liu, Jing & Zeng, Qing & Wu, Lan, 2022. "VIX and stock market volatility predictability: A new approach," Finance Research Letters, Elsevier, vol. 48(C).
    161. Shirui Wang & Tianyang Zhang, 2024. "Predictability of commodity futures returns with machine learning models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 302-322, February.
    162. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    163. Baetje, Fabian & Menkhoff, Lukas, 2013. "Macro determinants of U.S. stock market risk premia in bull and bear markets," Hannover Economic Papers (HEP) dp-520, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    164. Narayan, Paresh Kumar & Narayan, Seema & Phan, Dinh Hoang Bach, 2022. "Terrorism and international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    165. Jiqian Wang & Rangan Gupta & Oğuzhan Çepni & Feng Ma, 2023. "Forecasting international REITs volatility: the role of oil-price uncertainty," The European Journal of Finance, Taylor & Francis Journals, vol. 29(14), pages 1579-1597, September.
    166. Wang, Jianqiu & Wu, Ke & Tong, Guoshi & Chen, Dongxu, 2023. "Nonlinearity in the cross-section of stock returns: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 174-205.
    167. Panpan Zhu & Xing Zhang & You Wu & Hao Zheng & Yinpeng Zhang, 2021. "Investor attention and cryptocurrency: Evidence from the Bitcoin market," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-28, February.
    168. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    169. Arabinda Basistha & Richard Startz, 2024. "Measuring persistent global economic factors with output, commodity price, and commodity currency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2860-2885, November.
    170. Wan, Runqing & Fulop, Andras & Li, Junye, 2022. "Real-time Bayesian learning and bond return predictability," Journal of Econometrics, Elsevier, vol. 230(1), pages 114-130.
    171. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    172. Yaojie Zhang & Yu Wei & Li Liu, 2019. "Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1425-1438, September.
    173. Charles, Amelie & Darne, Olivier & Kim, Jae, 2016. "Stock Return Predictability: Evaluation based on Prediction Intervals," MPRA Paper 70143, University Library of Munich, Germany.
    174. Chen, Yan & Qiao, Gaoxiu & Zhang, Feipeng, 2022. "Oil price volatility forecasting: Threshold effect from stock market volatility," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    175. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    176. José Afonso Faias & Tiago Castel-Branco, 2018. "Out-Of-Sample Stock Return Prediction Using Higher-Order Moments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(06), pages 1-27, September.
    177. Chao Liang & Yaojie Zhang & Xiafei Li & Feng Ma, 2022. "Which predictor is more predictive for Bitcoin volatility? And why?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1947-1961, April.
    178. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
    179. Sharma, Susan Sunila, 2016. "Can consumer price index predict gold price returns?," Economic Modelling, Elsevier, vol. 55(C), pages 269-278.
    180. Cheng, WeiJin & Ming, Kai & Ullah, Mirzat, 2024. "Oil price volatility prediction using out-of-sample analysis – Prediction efficiency of individual models, combination methods, and machine learning based shrinkage methods," Energy, Elsevier, vol. 300(C).
    181. Byrne, Joseph P & Korobilis, Dimitris & Ribeiro, Pinho J, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," MPRA Paper 58956, University Library of Munich, Germany.
    182. Xu, Yanyan & Liu, Jing & Ma, Feng & Chu, Jielei, 2024. "Liquidity and realized volatility prediction in Chinese stock market: A time-varying transitional dynamic perspective," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 543-560.
    183. Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    184. Fong, Tom Pak Wing & Wu, Shui Tang, 2020. "Predictability in sovereign bond returns using technical trading rules: Do developed and emerging markets differ?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    185. José Afonso Faias & Juan Arismendi Zambrano, 2022. "Equity Risk Premium Predictability from Cross-Sectoral Downturns [International asset allocation with regime shifts]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 808-842.
    186. Lin, Hai & Tao, Xinyuan & Wu, Chunchi, 2022. "Forecasting earnings with combination of analyst forecasts," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 133-159.
    187. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    188. Lee, Ji Hyung & Shin, Youngki, 2023. "Complete Subset Averaging For Quantile Regressions," Econometric Theory, Cambridge University Press, vol. 39(1), pages 146-188, February.
    189. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    190. Honghai Yu & Xianfeng Hao & Liangyu Wu & Yuqi Zhao & Yudong Wang, 2023. "Eye in outer space: satellite imageries of container ports can predict world stock returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    191. Long, Huaigang & Zaremba, Adam & Zhou, Wenyu & Bouri, Elie, 2022. "Macroeconomics matter: Leading economic indicators and the cross-section of global stock returns," Journal of Financial Markets, Elsevier, vol. 61(C).
    192. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    193. Felix Haase, 2024. "Sum-of-the-Parts Revised: Economic Regimes and Flexible Probabilities," Research Papers in Economics 2024-10, University of Trier, Department of Economics.
    194. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    195. Peter Reinhard HANSEN & Allan TIMMERMANN, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," Economics Working Papers ECO2012/10, European University Institute.
    196. Zhen Cao & Jiancheng Shen & Xinbei Wei & Qunzi Zhang, 2023. "Anger in predicting the index futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 437-454, April.
    197. Joelle Miffre & Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2023. "The commodity risk premium and neural networks," Post-Print hal-04322519, HAL.
    198. Apergis Nicholas, 2021. "Forecasting US overseas travelling with univariate and multivariate models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 963-976, September.
    199. Chen, Yong & Eaton, Gregory W. & Paye, Bradley S., 2018. "Micro(structure) before macro? The predictive power of aggregate illiquidity for stock returns and economic activity," Journal of Financial Economics, Elsevier, vol. 130(1), pages 48-73.
    200. Haibin Xie & Yuying Sun & Pengying Fan, 2023. "Return direction forecasting: a conditional autoregressive shape model with beta density," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    201. Hollstein, Fabian & Prokopczuk, Marcel & Tharann, Björn & Wese Simen, Chardin, 2021. "Predictability in commodity markets: Evidence from more than a century," Journal of Commodity Markets, Elsevier, vol. 24(C).
    202. Atanasov, Victoria, 2021. "Unemployment and aggregate stock returns," Journal of Banking & Finance, Elsevier, vol. 129(C).
    203. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
    204. Ye, Wuyi & Guo, Ranran & Deschamps, Bruno & Jiang, Ying & Liu, Xiaoquan, 2021. "Macroeconomic forecasts and commodity futures volatility," Economic Modelling, Elsevier, vol. 94(C), pages 981-994.
    205. Antonios K. Alexandridis & Ekaterini Panopoulou & Ioannis Souropanis, 2024. "Forecasting exchange rates: An iterated combination constrained predictor approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 983-1017, July.
    206. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    207. Ma, Feng & Wu, Hanlin & Zeng, Qing, 2024. "Biodiversity and stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    208. Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
    209. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: what gain for investors?," Working Papers fe_2013_02, Deakin University, Department of Economics.
    210. Alena Audzeyeva & Xu Wang, 2023. "Fundamentals, real-time uncertainty and CDS index spreads," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 1-33, July.
    211. Mengxi He & Yaojie Zhang & Yudong Wang & Danyan Wen, 2024. "Modelling and forecasting crude oil price volatility with climate policy uncertainty," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    212. Davide Pettenuzzo & Allan Timmermann & Rossen Valkanov, 2013. "Forecasting Stock Returns under Economic Constraints," Working Papers 57, Brandeis University, Department of Economics and International Business School.
    213. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
    214. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    215. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    216. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Long, Jian-You & Zhou, Yang, 2023. "Forecasting stock market volatility under parameter and model uncertainty," Research in International Business and Finance, Elsevier, vol. 66(C).
    217. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    218. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    219. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    220. Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
    221. Siddhartha Chib & Simon C. Smith, 2024. "Factor Selection and Structural Breaks," Finance and Economics Discussion Series 2024-037, Board of Governors of the Federal Reserve System (U.S.).
    222. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2021. "Forecasting the Artificial Intelligence Index Returns: A Hybrid Approach," Working Papers 202182, University of Pretoria, Department of Economics.
    223. Guo, Xu & Wu, Chunchi, 2019. "Short interest, stock returns and credit ratings," Journal of Banking & Finance, Elsevier, vol. 108(C).
    224. Pyun, Sungjune, 2019. "Variance risk in aggregate stock returns and time-varying return predictability," Journal of Financial Economics, Elsevier, vol. 132(1), pages 150-174.
    225. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    226. Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
    227. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2022. "Forecasting With Panel Data: Estimation Uncertainty Versus Parameter Heterogeneity," CESifo Working Paper Series 9690, CESifo.
    228. Jonathan Fletcher, 2022. "Exploring the diversification benefits of US international equity closed-end funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 297-320, September.
    229. Langlois, Hugues, 2020. "Measuring skewness premia," Journal of Financial Economics, Elsevier, vol. 135(2), pages 399-424.
    230. Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
    231. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    232. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    233. Luo, Tao & Sun, Huaping & Zhang, Lixia & Bai, Jiancheng, 2024. "Do the dynamics of macroeconomic attention drive the yen/dollar exchange market volatility?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 597-611.
    234. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    235. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    236. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    237. Kartikay Gupta & Niladri Chatterjee, 2021. "Stocks Recommendation from Large Datasets Using Important Company and Economic Indicators," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 667-689, December.
    238. Wei, Yu & Liang, Chao & Li, Yan & Zhang, Xunhui & Wei, Guiwu, 2020. "Can CBOE gold and silver implied volatility help to forecast gold futures volatility in China? Evidence based on HAR and Ridge regression models," Finance Research Letters, Elsevier, vol. 35(C).
    239. Dragon Yongjun Tang, 2014. "Potential losses from incorporating return predictability into portfolio allocation," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 35-45, February.
    240. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    241. Biswas, Anindya, 2014. "The output gap and expected security returns," Review of Financial Economics, Elsevier, vol. 23(3), pages 131-140.
    242. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
    243. Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    244. Wang, Zijun & Qian, Yan & Wang, Shiwen, 2018. "Dynamic trading volume and stock return relation: Does it hold out of sample?," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 195-210.
    245. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
    246. Fameliti Stavroula & Skintzi Vasiliki, 2024. "Macroeconomic attention and commodity market volatility," Empirical Economics, Springer, vol. 67(5), pages 1967-2007, November.
    247. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
    248. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    249. Wei, Wei & Zhu, Dan, 2022. "Generic improvements to least squares monte carlo methods with applications to optimal stopping problems," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1132-1144.
    250. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    251. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    252. Hao, Xianfeng & Zhao, Yuyang & Wang, Yudong, 2020. "Forecasting the real prices of crude oil using robust regression models with regularization constraints," Energy Economics, Elsevier, vol. 86(C).
    253. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
    254. Reichlin, Lucrezia & Andreini, Paolo & Hasenzagl, Thomas & Senftleben-König, Charlotte & Strohsal, Till, 2020. "Nowcasting German GDP," CEPR Discussion Papers 14323, C.E.P.R. Discussion Papers.
    255. Wang, Cindy S.H. & Chen, Yi-Chi & Lo, Hsin-Yu, 2021. "A fresh look at the risk-return tradeoff," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    256. Yu, Miao & Song, Jinguo, 2018. "Volatility forecasting: Global economic policy uncertainty and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 316-323.
    257. Vassilis Polimenis & Ioannis Neokosmidis, 2019. "Non-stationary dividend-price ratios," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 552-567, December.
    258. Chao Liang & Feng Ma & Lu Wang & Qing Zeng, 2021. "The information content of uncertainty indices for natural gas futures volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1310-1324, November.
    259. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    260. James Yae & Yang Luo, 2023. "Robust monitoring machine: a machine learning solution for out-of-sample R $$^2$$ 2 -hacking in return predictability monitoring," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    261. Junyu Zhang & Xinfeng Ruan & Jin E. Zhang, 2023. "Risk‐neutral moments and return predictability: International evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1086-1111, August.
    262. Chao, Shih-Wei, 2016. "Do economic variables improve bond return volatility forecasts?," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 10-26.
    263. Zhu, Jiaji & Han, Wei & Zhang, Junchao, 2023. "Does climate risk matter for gold price volatility?," Finance Research Letters, Elsevier, vol. 58(PC).
    264. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    265. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    266. John Cotter & Mark Hallam & Kamil Yilmaz, 2020. "Macro-Financial Spillovers," Working Papers 202005, Geary Institute, University College Dublin.
    267. Han, Yang & Jiao, Anqi & Ma, Jun, 2021. "The predictive power of Nelson–Siegel factor loadings for the real economy," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 95-127.
    268. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Westerlund, Joakim, 2016. "Are Islamic stock returns predictable? A global perspective," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 210-223.
    269. Kae‐Yih Tzeng, 2023. "The ability of U.S. macroeconomic variables to predict Asian financial market returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3529-3551, October.
    270. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    271. Marie-Hélène Gagnon & Gabriel Power & Dominique Toupin, 2018. "Forecasting International Index Returns using Option-implied Variables," Cahiers de recherche 1807, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    272. Liu, Li & Ma, Feng & Wang, Yudong, 2015. "Forecasting excess stock returns with crude oil market data," Energy Economics, Elsevier, vol. 48(C), pages 316-324.
    273. Bakshi, Gurdip & Panayotov, George & Skoulakis, Georgios, 2011. "Improving the predictability of real economic activity and asset returns with forward variances inferred from option portfolios," Journal of Financial Economics, Elsevier, vol. 100(3), pages 475-495, June.
    274. Narayan, Paresh Kumar & Sharma, Susan Sunila & Phan, Dinh Hoang Bach, 2016. "Asset price bubbles and economic welfare," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 139-148.
    275. Liu, Chu-An & Kuo, Biing-Shen, 2014. "Model Averaging in Predictive Regressions," MPRA Paper 54198, University Library of Munich, Germany.
    276. Ren, Yu & Liang, Xuanxuan & Wang, Qin, 2021. "Short-term exchange rate forecasting: A panel combination approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    277. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    278. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
    279. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    280. Chao Liang & Yongan Xu & Zhonglu Chen & Xiafei Li, 2023. "Forecasting China's stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3689-3699, October.
    281. Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
    282. Yuan, Xianghui & Li, Xiang, 2022. "Delta-hedging demand and intraday momentum: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    283. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Stock return forecasting: Some new evidence," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 38-51.
    284. Zhang, Chu & Zhao, Shen, 2023. "The macroeconomic announcement premium and information environment," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 55-73.
    285. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.
    286. Wang, Jue & Zhou, Hao & Hong, Tao & Li, Xiang & Wang, Shouyang, 2020. "A multi-granularity heterogeneous combination approach to crude oil price forecasting," Energy Economics, Elsevier, vol. 91(C).
    287. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    288. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    289. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    290. Brückbauer, Frank, 2022. "Do financial market experts know their theory? New evidence from survey data," ZEW Discussion Papers 20-092, ZEW - Leibniz Centre for European Economic Research, revised 2022.
    291. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    292. Michael S. O'Doherty, 2012. "On the Conditional Risk and Performance of Financially Distressed Stocks," Management Science, INFORMS, vol. 58(8), pages 1502-1520, August.
    293. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    294. Chen, Xingyi & Li, Haiqi & Zhang, Jing, 2023. "Complete subset averaging approach for high-dimensional generalized linear models," Economics Letters, Elsevier, vol. 226(C).
    295. Lin, Qi & Lin, Xi, 2021. "Are the profitability and investment factors valid ICAPM risk factors? Pre-1963 evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    296. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
    297. Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
    298. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
    299. Zhang, Hongwei & Zhao, Xinyi & Gao, Wang & Niu, Zibo, 2023. "The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models," Journal of Commodity Markets, Elsevier, vol. 32(C).
    300. Qian, Lihua & Zeng, Qing & Lu, Xinjie & Ma, Feng, 2022. "Global tail risk and oil return predictability," Finance Research Letters, Elsevier, vol. 47(PB).
    301. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    302. Buncic, Daniel & Piras, Gion Donat, 2016. "Heterogeneous agents, the financial crisis and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 313-359.
    303. Huang, Dashan & Jiang, Fuwei & Li, Kunpeng & Tong, Guoshi & Zhou, Guofu, 2023. "Are bond returns predictable with real-time macro data?," Journal of Econometrics, Elsevier, vol. 237(2).
    304. Jongho Kang & Jangkoo Kang & Jaeram Lee, 2022. "Who and what drives informed options trading after the market opens?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 338-364, March.
    305. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    306. Ana Sequeira, 2013. "Predicting aggregate returns using valuation ratios out-of-sample," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    307. Warusawitharana, Missaka, 2013. "The expected real return to equity," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1929-1946.
    308. Patrick Bielstein, 2018. "International asset allocation using the market implied cost of capital," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(1), pages 17-51, February.
    309. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.
    310. Fei Lu & Feng Ma & Elie Bouri, 2024. "Stock market volatility predictability: new evidence from energy consumption," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    311. Nima Nonejad, 2021. "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, vol. 61(2), pages 973-1009, August.
    312. Tianlun Fei & Xiaoquan Liu & Conghua Wen, 2023. "Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1594-1621, November.
    313. Procasky, William J. & Yin, Anwen, 2023. "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    314. Harald Kinateder & Vassilios G. Papavassiliou, 2019. "Sovereign bond return prediction with realized higher moments," Open Access publications 10197/11286, Research Repository, University College Dublin.
    315. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    316. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    317. Hai Lin & Xinyuan Tao & Junbo Wang & Chunchi Wu, 2020. "Credit Spreads, Business Conditions, and Expected Corporate Bond Returns," JRFM, MDPI, vol. 13(2), pages 1-34, January.
    318. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
    319. Tom Engsted & Stig V. Møller & Magnus Sander, 2013. "Bond return predictability in expansions and recessions," CREATES Research Papers 2013-13, Department of Economics and Business Economics, Aarhus University.
    320. Liu, Zhichao & Xu, Xiulian & Cheng, Ya & Xie, Xuan, 2023. "Geopolitical risk of oil export and import countries and oil futures volatility: Evidence from dynamic model average methods," Finance Research Letters, Elsevier, vol. 54(C).
    321. Zhang, Keyi & Gençay, Ramazan & Ege Yazgan, M., 2017. "Application of wavelet decomposition in time-series forecasting," Economics Letters, Elsevier, vol. 158(C), pages 41-46.
    322. Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
    323. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    324. Bryan Kelly & Semyon Malamud & Kangying Zhou, 2024. "The Virtue of Complexity in Return Prediction," Journal of Finance, American Finance Association, vol. 79(1), pages 459-503, February.
    325. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2021. "Commodity futures returns and policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 364-383.
    326. Shang, Yue & Wei, Yu & Chen, Yongfei, 2022. "Cryptocurrency policy uncertainty and gold return forecasting: A dynamic Occam's window approach," Finance Research Letters, Elsevier, vol. 50(C).
    327. Qiu, Rui & Liu, Jing & Li, Yan, 2023. "Long-term adjusted volatility: Powerful capability in forecasting stock market returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    328. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    329. Peng, Lijuan & Liang, Chao, 2023. "Sustainable development during the post-COVID-19 period: Role of crude oil," Resources Policy, Elsevier, vol. 85(PA).
    330. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    331. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    332. Eirini Konstantinidi & George Skiadopoulos, 2014. "How Does the Market Variance Risk Premium Vary over Time? Evidence from S&P 500 Variance Swap Investment Returns," Working Papers 732, Queen Mary University of London, School of Economics and Finance.
    333. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    334. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
    335. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    336. Nguyet Nguyen, 2018. "Hidden Markov Model for Stock Trading," IJFS, MDPI, vol. 6(2), pages 1-17, March.
    337. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    338. Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023. "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 358-368.
    339. Hongwei Zhang & Qiang He & Ben Jacobsen & Fuwei Jiang, 2020. "Forecasting stock returns with model uncertainty and parameter instability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 629-644, August.
    340. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    341. Fabian Hollstein & Marcel Prokopczuk & Björn Tharann & Chardin Wese Simen, 2019. "Predicting the equity market with option-implied variables," The European Journal of Finance, Taylor & Francis Journals, vol. 25(10), pages 937-965, July.
    342. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    343. Becker, Janis & Leschinski, Christian, 2018. "Directional Predictability of Daily Stock Returns," Hannover Economic Papers (HEP) dp-624, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    344. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    345. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    346. Jonathan Dark & Xin Gao & Thijs van der Heijden & Federico Nardari, 2022. "Forecasting variance swap payoffs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2135-2164, December.
    347. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Forecasting the CNY-CNH pricing differential: The role of investor attention," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 232-247.
    348. Zhang, Li & Wang, Lu & Peng, Lijuan & Luo, Keyu, 2023. "Measuring the response of clean energy stock price volatility to extreme shocks," Renewable Energy, Elsevier, vol. 206(C), pages 1289-1300.
    349. Li, Dakai, 2024. "Forecasting stock market realized volatility: The role of investor attention to the price of petroleum products," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 115-122.
    350. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," University of California at San Diego, Economics Working Paper Series qt1st3n7z7, Department of Economics, UC San Diego.
    351. Jin, Daxiang & He, Mengxi & Xing, Lu & Zhang, Yaojie, 2022. "Forecasting China's crude oil futures volatility: How to dig out the information of other energy futures volatilities?," Resources Policy, Elsevier, vol. 78(C).
    352. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    353. Nuno Silva, 2015. "Industry based equity premium forecasts," GEMF Working Papers 2015-19, GEMF, Faculty of Economics, University of Coimbra.
    354. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    355. Zhifeng Dai & Jie Kang & Hua Yin, 2023. "Forecasting equity risk premium: A new method based on wavelet de‐noising," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4331-4352, October.
    356. Dladla, Pholile & Malikane, Christopher, 2019. "Stock return predictability: Evidence from a structural model," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 412-424.
    357. Buncic, Daniel & Moretto, Carlo, 2014. "Forecasting Copper Prices with Dynamic Averaging and Selection Models," Economics Working Paper Series 1430, University of St. Gallen, School of Economics and Political Science.
    358. Chen, Ding & Guo, Biao & Zhou, Guofu, 2023. "Firm fundamentals and the cross-section of implied volatility shapes," Journal of Financial Markets, Elsevier, vol. 63(C).
    359. Dai, Zhifeng & Zhou, Huiting & Kang, Jie & Wen, Fenghua, 2021. "The skewness of oil price returns and equity premium predictability," Energy Economics, Elsevier, vol. 94(C).
    360. Chiah, Mardy & Phan, Dinh Hoang Bach & Tran, Vuong Thao & Zhong, Angel, 2022. "Energy price uncertainty and the value premium," International Review of Financial Analysis, Elsevier, vol. 81(C).
    361. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    362. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.
    363. Yongsheng Yi & Feng Ma & Dengshi Huang & Yaojie Zhang, 2019. "Interest rate level and stock return predictability," Review of Financial Economics, John Wiley & Sons, vol. 37(4), pages 506-522, October.
    364. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    365. Nonejad, Nima, 2022. "Equity premium prediction using the price of crude oil: Uncovering the nonlinear predictive impact," Energy Economics, Elsevier, vol. 115(C).
    366. Wang, Yuejing & Ye, Wuyi & Jiang, Ying & Liu, Xiaoquan, 2024. "Volatility prediction for the energy sector with economic determinants: Evidence from a hybrid model," International Review of Financial Analysis, Elsevier, vol. 92(C).
    367. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    368. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    369. Matthias Kruttli & Andrew J. Patton & Tarun Ramadorai, 2013. "The Impact of Hedge Funds on Asset Markets," Working Papers 13-27, Duke University, Department of Economics.
    370. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    371. Gunter Löffler, 2013. "Tower Building And Stock Market Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 36(3), pages 413-434, September.
    372. Liu, Jing & He, Qiubei & Li, Yan & Huynh, Luu Duc Toan & Liang, Chao, 2023. "The change in stock-selection risk and stock market returns," International Review of Financial Analysis, Elsevier, vol. 85(C).
    373. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    374. Dai, Zhifeng & Zhu, Huan & Kang, Jie, 2021. "New technical indicators and stock returns predictability," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 127-142.
    375. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment," Working Papers 202247, University of Pretoria, Department of Economics.
    376. Liyan Han & Xinbei Wei & Sen Yan & Qunzi Zhang, 2022. "Analyst rating matters for index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2084-2100, November.
    377. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    378. Faria, Gonçalo & Verona, Fabio, 2024. "Unlocking predictive potential: the frequency-domain approach to equity premium forecasting," Bank of Finland Research Discussion Papers 10/2024, Bank of Finland.
    379. Li Liu & Yudong Wang, 2021. "Forecasting aggregate market volatility: The role of good and bad uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 40-61, January.
    380. Ruan, Xinfeng & Zhang, Jin E., 2019. "Moment spreads in the energy market," Energy Economics, Elsevier, vol. 81(C), pages 598-609.
    381. Sang Il Lee, 2020. "Deeply Equal-Weighted Subset Portfolios," Papers 2006.14402, arXiv.org.
    382. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    383. Jia, Xiaolan & Ruan, Xinfeng & Zhang, Jin E., 2023. "Carr and Wu’s (2020) framework in the oil ETF option market," Journal of Commodity Markets, Elsevier, vol. 31(C).
    384. Dai, Zhifeng & Zhang, Xiaotong & Liang, Chao, 2024. "Efficient predictability of oil price: The role of VIX-based panic index shadow line difference," Energy Economics, Elsevier, vol. 129(C).
    385. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).
    386. Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
    387. Fletcher, Jonathan, 2021. "International equity U.S. mutual funds and diversification benefits," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 246-257.
    388. Richard Anthony Kent & Di Bu, 2020. "The importance of cash flow disclosure and cost of capital," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 877-908, April.
    389. Kuppenheimer, Gregory & Shelly, Stuart & Strauss, Jack, 2023. "Can machine learning identify sector-level financial ratios that predict sector returns?," Finance Research Letters, Elsevier, vol. 57(C).
    390. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    391. Alexander M. Chinco & Adam D. Clark-Joseph & Mao Ye, 2017. "Sparse Signals in the Cross-Section of Returns," NBER Working Papers 23933, National Bureau of Economic Research, Inc.
    392. Polimenis, Vassilis & Neokosmidis, Ioannis M., 2016. "The modified dividend–price ratio," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 31-38.
    393. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
    394. Goodness C. Aye & Rangan Gupta & Mampho P. Modise, 2012. "Structural Breaks and Predictive Regressions Models of South African Equity Premium," Working Papers 201209, University of Pretoria, Department of Economics.
    395. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
    396. Prabhu Prasad Panda & Maysam Khodayari Gharanchaei & Xilin Chen & Haoshu Lyu, 2024. "Application of Deep Learning for Factor Timing in Asset Management," Papers 2404.18017, arXiv.org.
    397. Yu, Honghai & Du, Donglei & Fang, Libing & Yan, Panpan, 2018. "Risk contribution of crude oil to industry stock returns," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 179-199.
    398. Lutzenberger, Fabian T., 2014. "The predictability of aggregate returns on commodity futures," Review of Financial Economics, Elsevier, vol. 23(3), pages 120-130.
    399. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    400. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    401. Chen Gu & Xu Guo & Alexander Kurov & Raluca Stan, 2022. "The information content of the volatility index options trading volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(9), pages 1721-1737, September.
    402. Jianhui Li & Sebastian A. Gehricke & Jin E. Zhang, 2019. "How do US options traders “smirk” on China? Evidence from FXI options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1450-1470, November.
    403. Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
    404. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    405. Emmanuel Thompson & Ahmad M. Talafha, 2017. "Forecasting a Composite Indicator of Economic Activity in Ghana: A Comparison of Data Science Methods," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(4), pages 1-2.
    406. Stig V. Møller & Jesper Rangvid, 2018. "Global Economic Growth and Expected Returns Around the World: The End-of-the-Year Effect," Management Science, INFORMS, vol. 64(2), pages 573-591, February.
    407. Ahmed, Walid M.A. & Al Mafrachi, Mustafa, 2021. "Do higher-order realized moments matter for cryptocurrency returns?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 483-499.
    408. Masud Alam, 2024. "Volatility in U.S. Housing Sector and the REIT Equity Return," The Journal of Real Estate Finance and Economics, Springer, vol. 69(3), pages 505-544, October.
    409. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Multi-factor volatility and stock returns," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 132-149.
    410. Nicholas Taylor, 2014. "The Economic Value of Volatility Forecasts: A Conditional Approach," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 433-478.
    411. Qian Han & Jufang Liang & Boqiang Wu, 2016. "Cross Economic Determinants of Implied Volatility Smile Dynamics: Three Major European Currency Options," European Financial Management, European Financial Management Association, vol. 22(5), pages 817-852, November.
    412. Zhang, Lei & Chen, Yan & Bouri, Elie, 2024. "Time-varying jump intensity and volatility forecasting of crude oil returns," Energy Economics, Elsevier, vol. 129(C).
    413. Choi, Jin Ho & Suh, Sangwon, 2021. "A filtered currency carry trade," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    414. Poshakwale, Sunil S. & Chandorkar, Pankaj & Agarwal, Vineet, 2019. "Implied volatility and the cross section of stock returns in the UK," Research in International Business and Finance, Elsevier, vol. 48(C), pages 271-286.
    415. David E. Rapach & Matthew C. Ringgenberg & Guofu Zhou, 2016. "Short interest and aggregate stock returns," CEMA Working Papers 716, China Economics and Management Academy, Central University of Finance and Economics.
    416. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
    417. Bergbrant, Mikael & Kassa, Haimanot, 2021. "Is idiosyncratic volatility related to returns? Evidence from a subset of firms with quality idiosyncratic volatility estimates," Journal of Banking & Finance, Elsevier, vol. 127(C).
    418. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    419. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    420. Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
    421. Lahr, Henry & Trombley, Timothy E., 2020. "Early indicators of fundraising success by venture capital firms," Journal of Corporate Finance, Elsevier, vol. 65(C).
    422. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    423. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    424. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    425. Thorsten Lehnert & Gildas Blanchard & Dennis Bams, 2014. "Evaluating Option Pricing Model Performance Using Model Uncertainty," LSF Research Working Paper Series 14-06, Luxembourg School of Finance, University of Luxembourg.
    426. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    427. Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2016. "Evaluating Hedge Funds with Pooled Benchmarks," Management Science, INFORMS, vol. 62(1), pages 69-89, January.
    428. Awijen, Haithem & Ben Zaied, Younes & Ben Lahouel, Béchir & Khlifi, Foued, 2023. "Machine learning for US cross-industry return predictability under information uncertainty," Research in International Business and Finance, Elsevier, vol. 64(C).
    429. Ghani, Maria & Guo, Qiang & Ma, Feng & Li, Tao, 2022. "Forecasting Pakistan stock market volatility: Evidence from economic variables and the uncertainty index," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1180-1189.
    430. Andrew Detzel & Jack Strauss, 2018. "Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1949-1973.
    431. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    432. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    433. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    434. Weidong Tian & Qing Zhou, 2017. "Asset Pricing Model Uncertainty: A Tradeoff between Bias and Variance," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 289-324, June.
    435. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    436. Carlos Carvalho & Jared D. Fisher & Davide Pettenuzzo, 2018. "Optimal Asset Allocation with Multivariate Bayesian Dynamic Linear Models," Working Papers 123, Brandeis University, Department of Economics and International Business School.
    437. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
    438. Song, Ziyu & Yu, Changrui, 2022. "Investor sentiment indices based on k-step PLS algorithm: A group of powerful predictors of stock market returns," International Review of Financial Analysis, Elsevier, vol. 83(C).
    439. Li, Hongchang & Strauss, Jack & Shunxiang, Hu & Lui, Lu, 2018. "Do high-speed railways lead to urban economic growth in China? A panel data study of China’s cities," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 70-89.
    440. Golab, Anna & Bannigidadmath, Deepa & Pham, Thach Ngoc & Thuraisamy, Kannan, 2022. "Economic policy uncertainty and industry return predictability – Evidence from the UK," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 433-447.
    441. Li, Yan & Ng, David T. & Swaminathan, Bhaskaran, 2013. "Predicting market returns using aggregate implied cost of capital," Journal of Financial Economics, Elsevier, vol. 110(2), pages 419-436.
    442. Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
    443. Luo, Qin & Ma, Feng & Wang, Jiqian & Wu, You, 2024. "Changing determinant driver and oil volatility forecasting: A comprehensive analysis," Energy Economics, Elsevier, vol. 129(C).
    444. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    445. Lin, Hai & Wang, Junbo & Wu, Chunchi, 2014. "Predictions of corporate bond excess returns," Journal of Financial Markets, Elsevier, vol. 21(C), pages 123-152.
    446. Boucher, C. & Jasinski, A. & Tokpavi, S., 2023. "Conditional mean reversion of financial ratios and the predictability of returns," Journal of International Money and Finance, Elsevier, vol. 137(C).
    447. Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
    448. Biao Guo & Qian Han & Hai Lin, 2018. "Are there gains from using information over the surface of implied volatilities?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 645-672, June.
    449. Jozef Barunik & Mattia Bevilacqua & Robert Faff, 2021. "Dynamic industry uncertainty networks and the business cycle," Papers 2101.06957, arXiv.org, revised Mar 2021.
    450. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    451. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    452. Roberto Gómez‐Cram, 2022. "Late to Recessions: Stocks and the Business Cycle," Journal of Finance, American Finance Association, vol. 77(2), pages 923-966, April.
    453. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    454. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    455. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2014. "Firm return volatility and economic gains: The role of oil prices," Economic Modelling, Elsevier, vol. 38(C), pages 142-151.
    456. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
    457. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2015. "Market Sentiment and Paradigm Shifts," Research Paper Series 356, Quantitative Finance Research Centre, University of Technology, Sydney.
    458. Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018. "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, vol. 70(C), pages 472-483.
    459. Di Bu & Simone Kelly & Yin Liao & Qing Zhou, 2018. "A hybrid information approach to predict corporate credit risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1062-1078, September.
    460. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    461. Ribeiro, Pinho J., 2017. "Selecting exchange rate fundamentals by bootstrap," International Journal of Forecasting, Elsevier, vol. 33(4), pages 894-914.
    462. Chen, An-Sing & Chang, Hung-Chou & Cheng, Lee-Young, 2019. "Time-varying Variance Scaling: Application of the Fractionally Integrated ARMA Model," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 1-12.
    463. Tae-Hwy Lee & Eric Hillebrand & Marcelo Medeiros, 2014. "Bagging Constrained Equity Premium Predictors," Working Papers 201421, University of California at Riverside, Department of Economics, revised Feb 2013.
    464. Westerlund, Joakim & Narayan, Paresh, 2016. "Testing for predictability in panels of any time series dimension," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1162-1177.
    465. Pan, Wei-Fong, 2018. "Evidence of Investor Sentiment Contagion across Asset Markets," MPRA Paper 88561, University Library of Munich, Germany.
    466. Ghani, Usman & Zhu, Bo & Ghani, Maria & Khan, Nasir & khan, Raja Danish Akbar, 2023. "Role of oil shocks in US stock market volatility: A new insight from GARCH-MIDAS perspective," Resources Policy, Elsevier, vol. 85(PB).
    467. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    468. Ellington, Michael & Stamatogiannis, Michalis P. & Zheng, Yawen, 2022. "A study of cross-industry return predictability in the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 83(C).
    469. Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
    470. Anibal Emiliano Da Silva Neto & Jesús Gonzalo & Jean‐Yves Pitarakis, 2021. "Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 713-741, June.
    471. Jixiang, Zhang & Feng, Ma, 2024. "Video apps user engagement and stock market volatility: Evidence from China," Finance Research Letters, Elsevier, vol. 64(C).
    472. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    473. Iuliia Brushko, 2013. "Financial Signaling and Earnings Forecasts," CERGE-EI Working Papers wp498, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    474. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
    475. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2016. "Intraday return predictability, portfolio maximisation, and hedging," Emerging Markets Review, Elsevier, vol. 28(C), pages 105-116.
    476. Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
    477. de Oliveira Souza, Thiago, 2019. "Predictability concentrates in bad times. And so does disagreement," Discussion Papers on Economics 8/2019, University of Southern Denmark, Department of Economics.
    478. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Narayan, Seema, 2018. "Technology-investing countries and stock return predictability," Emerging Markets Review, Elsevier, vol. 36(C), pages 159-179.
    479. Yin, Libo & Yang, Zhichen, 2022. "The profitability effect: Insight from a dynamic perspective," International Review of Financial Analysis, Elsevier, vol. 80(C).
    480. Zhu, Min, 2013. "Return distribution predictability and its implications for portfolio selection," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 209-223.
    481. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    482. Li, Yan & Liang, Chao & Huynh, Toan Luu Duc, 2022. "Forecasting US stock market returns by the aggressive stock-selection opportunity," Finance Research Letters, Elsevier, vol. 50(C).
    483. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
    484. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    485. Zhang, Li & Liang, Chao & Huynh, Luu Duc Toan & Wang, Lu & Damette, Olivier, 2024. "Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies," Journal of Economic Behavior & Organization, Elsevier, vol. 223(C), pages 168-184.
    486. Ren, Xiaohang & Duan, Kun & Tao, Lizhu & Shi, Yukun & Yan, Cheng, 2022. "Carbon prices forecasting in quantiles," Energy Economics, Elsevier, vol. 108(C).
    487. Seda Oz & Steve Fortin, 2023. "Is it time for popcorn? Daily box office earnings and aggregate stock returns," Financial Management, Financial Management Association International, vol. 52(2), pages 375-401, June.
    488. Deaves, Richard & Lei, Jin & Schröder, Michael, 2015. "Forecaster overconfidence and market survey performance," ZEW Discussion Papers 15-029, ZEW - Leibniz Centre for European Economic Research.
    489. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.
    490. George Athanasopoulos & Rob J Hyndman & Raffaele Mattera, 2023. "Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering," Monash Econometrics and Business Statistics Working Papers 17/23, Monash University, Department of Econometrics and Business Statistics.
    491. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    492. Man Wang & Yihan Cheng, 2022. "Forecasting value at risk and expected shortfall using high‐frequency data of domestic and international stock markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1595-1607, December.
    493. Meng, Fanyi & Liu, Li, 2019. "Analyzing the economic sources of oil price volatility: An out-of-sample perspective," Energy, Elsevier, vol. 177(C), pages 476-486.
    494. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
    495. Lu, Fei & Ma, Feng & Hu, Shiyang, 2024. "Does energy consumption play a key role? Re-evaluating the energy consumption-economic growth nexus from GDP growth rates forecasting," Energy Economics, Elsevier, vol. 129(C).
    496. Zeng, Qing & Cao, Jiawei & Guo, Yangli & Dong, Dayong, 2023. "The macroeconomic attention index: Evidence from China," Finance Research Letters, Elsevier, vol. 52(C).
    497. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    498. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    499. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    500. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
    501. Andreini, Paolo & Hasenzagl, Thomas & Reichlin, Lucrezia & Senftleben-König, Charlotte & Strohsal, Till, 2023. "Nowcasting German GDP: Foreign factors, financial markets, and model averaging," International Journal of Forecasting, Elsevier, vol. 39(1), pages 298-313.
    502. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    503. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Dynamic factors and asset pricing: International and further U.S. evidence," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 21-39.
    504. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    505. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    506. Nonejad, Nima, 2018. "Déjà vol oil? Predicting S&P 500 equity premium using crude oil price volatility: Evidence from old and recent time-series data," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 260-270.
    507. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    508. Victoria Atanasov & Stig V. Møller & Richard Priestley, 2020. "Consumption Fluctuations and Expected Returns," Journal of Finance, American Finance Association, vol. 75(3), pages 1677-1713, June.
    509. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    510. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
    511. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    512. Ren‐Raw Chen & Pei‐Lin Hsieh & Jeffrey Huang & Xiaowei Li, 2023. "Predictive power of the implied volatility term structure in the fixed‐income market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 349-383, March.
    513. Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
    514. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    515. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    516. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    517. Yin, Ximing & Yang, Ge, 2024. "Instantaneous volatility of the yield curve, variance risk premium and bond return predictability," Journal of Empirical Finance, Elsevier, vol. 77(C).
    518. Xianfeng Hao & Yudong Wang, 2023. "Cloud cover and expected oil returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    519. Jia, Jian & Kang, Sang Baum, 2022. "Do the basis and other predictors of futures return also predict spot return with the same signs and magnitudes? Evidence from the LME," Journal of Commodity Markets, Elsevier, vol. 25(C).
    520. Thomas Trier Bjerring & Kourosh Marjani Rasmussen & Alex Weissensteiner, 2018. "Portfolio selection under supply chain predictability," Computational Management Science, Springer, vol. 15(2), pages 139-159, June.
    521. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
    522. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    523. Fabian Hollstein & Marcel Prokopczuk, 2023. "Managing the Market Portfolio," Management Science, INFORMS, vol. 69(6), pages 3675-3696, June.
    524. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    525. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2016. "Forecasting stock volatility using after-hour information: Evidence from the Australian Stock Exchange," Economic Modelling, Elsevier, vol. 52(PB), pages 592-608.
    526. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    527. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    528. Anwen Yin, 2019. "Equity Premium Prediction with Structural Breaks: A Two-Stage Forecast Combination Approach," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(12), pages 1-50, December.
    529. Bakshi, Gurdip & Panayotov, George, 2013. "Predictability of currency carry trades and asset pricing implications," Journal of Financial Economics, Elsevier, vol. 110(1), pages 139-163.
    530. Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
    531. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    532. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    533. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    534. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    535. Eriksen, Jonas N., 2017. "Expected Business Conditions and Bond Risk Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1667-1703, August.
    536. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2016. "Can commodity returns forecast Canadian sector stock returns?," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 172-188.
    537. Ji Ho Kwon, 2021. "On the factors of Bitcoin’s value at risk," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    538. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    539. Yigit Atilgan & K. Ozgur Demirtas & A. Doruk Gunaydin & Imra Kirli, 2023. "Average skewness in global equity markets," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 245-271, June.
    540. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    541. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
    542. Jack Strauss, 2017. "Do High Speed Railways Lead to Urban Economic Growth in China?," Proceedings of Economics and Finance Conferences 4807677, International Institute of Social and Economic Sciences.
    543. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    544. Bai, Fan & Zhang, Yaqi & Chen, Zhonglu & Li, Yan, 2023. "The volatility of daily tug-of-war intensity and stock market returns," Finance Research Letters, Elsevier, vol. 55(PA).
    545. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    546. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    547. Li, Xiaodan & Gong, Xue & Ge, Futing & Huang, Jingjing, 2024. "Forecasting stock volatility using pseudo-out-of-sample information," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 123-135.
    548. Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
    549. Zhang, Li & Wang, Lu & Wang, Xunxiao & Zhang, Yaojie & Pan, Zhigang, 2022. "How macro-variables drive crude oil volatility? Perspective from the STL-based iterated combination method," Resources Policy, Elsevier, vol. 77(C).
    550. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    551. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    552. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    553. Sultan Alturki & Alexander Kurov, 2022. "Market inefficiencies surrounding energy announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 172-188, January.
    554. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
    555. Philippe Goulet Coulombe & Maximilian Goebel, 2023. "Maximally Machine-Learnable Portfolios," Papers 2306.05568, arXiv.org, revised Apr 2024.
    556. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
    557. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    558. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    559. Chen Gu & Alexander Kurov, 2018. "What drives informed trading before public releases? Evidence from natural gas inventory announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1079-1096, September.
    560. Jungah Yoon & Xinfeng Ruan & Jin E. Zhang, 2022. "VIX option‐implied volatility slope and VIX futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1002-1038, June.
    561. Kartikay Gupta & Niladri Chatterjee, 2019. "Top performing stocks recommendation strategy for portfolio," Papers 1901.11013, arXiv.org, revised Aug 2019.
    562. Guanhao Feng & Jingyu He & Nicholas G. Polson, 2018. "Deep Learning for Predicting Asset Returns," Papers 1804.09314, arXiv.org, revised Apr 2018.
    563. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    564. Xiaolan Jia & Xinfeng Ruan & Jin E. Zhang, 2021. "The implied volatility smirk of commodity options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 72-104, January.
    565. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
    566. Zeng, Qing & Lu, Xinjie & Dong, Dayong & Li, Pan, 2022. "Category-specific EPU indices, macroeconomic variables and stock market return predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    567. Naresh Bansal & Jack Strauss & Alireza Nasseh, 2015. "Can we consistently forecast a firm’s earnings? Using combination forecast methods to predict the EPS of Dow firms," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(1), pages 1-22, January.
    568. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
    569. Ilias Tsiakas & Jiahan Li & Haibin Zhang, 2020. "Equity Premium Prediction and the State of the Economy," Working Paper series 20-16, Rimini Centre for Economic Analysis.
    570. Jonathan A. Batten & Harald Kinateder & Niklas Wagner, 2022. "Beating the Average: Equity Premium Variations, Uncertainty, and Liquidity," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 567-588, September.
    571. Opie, Wei & Riddiough, Steven J., 2020. "Global currency hedging with common risk factors," Journal of Financial Economics, Elsevier, vol. 136(3), pages 780-805.
    572. Lof, Matthijs & Nyberg, Henri, 2024. "Discount rates and cash flows: A local projection approach," Journal of Banking & Finance, Elsevier, vol. 162(C).
    573. Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
    574. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    575. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    576. Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
    577. Wang, Yudong & Geng, Qianjie & Meng, Fanyi, 2019. "Futures hedging in crude oil markets: A comparison between minimum-variance and minimum-risk frameworks," Energy, Elsevier, vol. 181(C), pages 815-826.
    578. Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2018. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Papers 1805.12217, arXiv.org, revised Jul 2019.
    579. Bruno Deschamps & Tianlun Fei & Ying Jiang & Xiaoquan Liu, 2022. "Procyclical volatility in Chinese stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1117-1144, April.
    580. Jahangir Sultan & Antonios K. Alexandridis & Mohammad Hasan & Xuxi Guo, 2019. "Hedging performance of multiscale hedge ratios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1613-1632, December.
    581. Wang, Jiashun & Wang, Jiqian & Ma, Feng, 2024. "International commodity market and stock volatility predictability: Evidence from G7 countries," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 62-71.
    582. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    583. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    584. Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    585. Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022. "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, vol. 62(C).
    586. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    587. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    588. Back, Kerry & Crotty, Kevin & Kazempour, Seyed Mohammad, 2022. "Validity, tightness, and forecasting power of risk premium bounds," Journal of Financial Economics, Elsevier, vol. 144(3), pages 732-760.
    589. Anwen Yin, 2024. "Predictive model averaging with parameter instability and heteroskedasticity," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 418-442, April.
    590. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
    591. Gao, Shang & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2023. "Forecasting stock market volatility: The sum of the parts is more than the whole," Finance Research Letters, Elsevier, vol. 55(PA).
    592. Hai Lin & Daniel Quill & Henk Berkman, 2016. "Information diffusion and the predictability of New Zealand stock market returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 749-785, September.
    593. Anindya Biswas, 2014. "The output gap and expected security returns," Review of Financial Economics, John Wiley & Sons, vol. 23(3), pages 131-140, September.
    594. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    595. Philippe Goulet Coulombe & Maximilian Gobel, 2023. "Maximally Machine-Learnable Portfolios," Working Papers 23-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Apr 2023.
    596. Zhu, Xiaoneng & Zhu, Jie, 2013. "Predicting stock returns: A regime-switching combination approach and economic links," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4120-4133.
    597. Narayan, Paresh Kumar & Ahmed, Huson Ali & Narayan, Seema, 2017. "Can investors gain from investing in certain sectors?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 160-177.
    598. Qianjie Geng & Yudong Wang, 2021. "Futures Hedging in CSI 300 Markets: A Comparison Between Minimum-Variance and Maximum-Utility Frameworks," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 719-742, February.
    599. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
    600. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    601. Narayan, Paresh Kumar & Narayan, Seema & Westerlund, Joakim, 2015. "Do order imbalances predict Chinese stock returns? New evidence from intraday data," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 136-151.
    602. Lu, Fei & Ma, Feng & Feng, Lin, 2024. "Carbon dioxide emissions and economic growth: New evidence from GDP forecasting," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    603. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    604. Bumho Son & Yunyoung Lee & Seongwan Park & Jaewook Lee, 2023. "Forecasting global stock market volatility: The impact of volatility spillover index in spatial‐temporal graph‐based model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1539-1559, November.
    605. Jiang, Fuwei & Ma, Tian & Zhu, Feifei, 2024. "Fundamental characteristics, machine learning, and stock price crash risk," Journal of Financial Markets, Elsevier, vol. 69(C).
    606. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    607. Fabian T. Lutzenberger, 2014. "The predictability of aggregate returns on commodity futures," Review of Financial Economics, John Wiley & Sons, vol. 23(3), pages 120-130, September.
    608. Andrew Y. Chen & Tom Zimmermann, 2022. "Publication Bias in Asset Pricing Research," Papers 2209.13623, arXiv.org, revised Sep 2023.
    609. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
    610. Guo, Xu & Lin, Hai & Wu, Chunchi & Zhou, Guofu, 2022. "Predictive information in corporate bond yields," Journal of Financial Markets, Elsevier, vol. 59(PB).
    611. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    612. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    613. Kuo, Chen-Yin, 2016. "Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory," Economic Modelling, Elsevier, vol. 52(PB), pages 772-789.
    614. An, Zhengzhen & Zhao, Yue & Zhang, Yanfei, 2023. "Mineral exploration and the green transition: Opportunities and challenges for the mining industry," Resources Policy, Elsevier, vol. 86(PA).
    615. Baur, Dirk G. & Löffler, Gunter, 2015. "Predicting the equity premium with the demand for gold coins and bars," Finance Research Letters, Elsevier, vol. 13(C), pages 172-178.
    616. Nusret Cakici & Christian Fieberg & Daniel Metko & Adam Zaremba, 2024. "Do Anomalies Really Predict Market Returns? New Data and New Evidence," Review of Finance, European Finance Association, vol. 28(1), pages 1-44.
    617. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
    618. Eduard Baitinger, 2021. "Forecasting asset returns with network‐based metrics: A statistical and economic analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1342-1375, November.
    619. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2023. "A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    620. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    621. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    622. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    623. Helmut Herwartz & Malte Rengel & Fang Xu, 2016. "Local Trends in Price‐to‐Dividend Ratios—Assessment, Predictive Value, and Determinants," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(8), pages 1655-1690, December.
    624. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.
    625. Møller, Stig V. & Sander, Magnus, 2017. "Dividends, earnings, and predictability," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 153-163.
    626. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    627. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    628. Hai Lin & Pengfei Liu & Cheng Zhang, 2023. "The trend premium around the world: Evidence from the stock market," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 317-358, June.
    629. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
    630. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
    631. Cao, Charles & Simin, Timothy & Xiao, Han, 2020. "Predicting the equity premium with the implied volatility spread," Journal of Financial Markets, Elsevier, vol. 51(C).
    632. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    633. Yuqing Feng & Yaojie Zhang & Yudong Wang, 2024. "Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 567-582, April.
    634. Liu, Na & Gao, Fumin, 2022. "The world uncertainty index and GDP growth rate," Finance Research Letters, Elsevier, vol. 49(C).
    635. Jiahan Li & Ilias Tsiakas & Wei Wang, 2015. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
    636. Cao, Charles & Simin, Timothy & Xiao, Han, 2019. "Predicting the equity premium with the implied volatility spread," MPRA Paper 103651, University Library of Munich, Germany.
    637. Lu, Fei & Ma, Feng & Bouri, Elie & Liao, Yin, 2024. "Do commodity futures have a steering effect on the spot stock market in China? New evidence from volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 94(C).
    638. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    639. Chao Liang & Yu Wei & Likun Lei & Feng Ma, 2022. "Global equity market volatility forecasting: New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 594-609, January.
    640. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
    641. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    642. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
    643. Maria Ghani & Usman Ghani, 2024. "Economic Policy Uncertainty and Emerging Stock Market Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(1), pages 165-181, March.
    644. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    645. Hui Zeng & Ben R Marshall & Nhut H Nguyen & Nuttawat Visaltanachoti, 2022. "Are individual stock returns predictable?," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 135-162, February.
    646. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    647. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    648. Pan, Zheyao & Chan, Kam Fong, 2018. "A new government bond volatility index predictor for the U.S. equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 200-215.
    649. Pan, Zhiyuan & Huang, Xiao & Liu, Li & Huang, Juan, 2023. "Geopolitical uncertainty and crude oil volatility: Evidence from oil-importing and oil-exporting countries," Finance Research Letters, Elsevier, vol. 52(C).
    650. Jian Chen & Yangshu Liu, 2020. "Bid and ask prices of index put options: Which predicts the underlying stock returns?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1337-1353, September.
    651. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
    652. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    653. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    654. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Variational inference for large Bayesian vector autoregressions," Papers 2202.12644, arXiv.org, revised Jun 2023.
    655. Alexandru MANOLE & Madalina-Gabriela ANGHEL & Ihab Jweida SJ JWEIDA & Radu STOICA & Emilia STANCIU, 2016. "Structural analysis of foreign trade of Romania," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(12), pages 21-31, December.
    656. Su, Kuangxi & Yao, Yinhong & Zheng, Chengli & Xie, Wenzhao, 2023. "A novel hybrid strategy for crude oil future hedging based on the combination of three minimum-CVaR models," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 35-50.
    657. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    658. Liu, Li & Pan, Zhiyuan, 2020. "Forecasting stock market volatility: The role of technical variables," Economic Modelling, Elsevier, vol. 84(C), pages 55-65.
    659. Adrian Fernandez‐Perez & Bart Frijns & Ilnara Gafiatullina & Alireza Tourani‐Rad, 2019. "Properties and the predictive power of implied volatility in the New Zealand dairy market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(5), pages 612-631, May.
    660. Dominik Wolff & Ulrich Neugebauer, 2019. "Tree-based machine learning approaches for equity market predictions," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 273-288, July.
    661. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    662. Hollyman, Ross & Petropoulos, Fotios & Tipping, Michael E., 2021. "Understanding forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 294(1), pages 149-160.
    663. Navratil, Robert & Taylor, Stephen & Vecer, Jan, 2021. "On equity market inefficiency during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 77(C).
    664. Yin, Libo & Wang, Yang, 2019. "Forecasting the oil prices: What is the role of skewness risk?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    665. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    666. Sakemoto, Ryuta, 2021. "Economic Evaluation of Cryptocurrency Investment," MPRA Paper 108283, University Library of Munich, Germany.
    667. Li, Xiaowei & Wu, Zhengyu & Zhang, Hao & Zhang, Lu, 2024. "Risk-neutral skewness and stock market returns: A time-series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    668. Zeng, Qing & Zhang, Jixiang & Zhong, Juandan, 2024. "China's futures market volatility and sectoral stock market volatility prediction," Energy Economics, Elsevier, vol. 132(C).
    669. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    670. Iyke, Bernard Njindan & Tran, Vuong Thao & Narayan, Paresh Kumar, 2021. "Can energy security predict energy stock returns?," Energy Economics, Elsevier, vol. 94(C).
    671. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    672. Zhou, Guofu, 2010. "How much stock return predictability can we expect from an asset pricing model?," Economics Letters, Elsevier, vol. 108(2), pages 184-186, August.
    673. Zeng, Qing & Lu, Xinjie & Li, Tao & Wu, Lan, 2022. "Jumps and stock market variance during the COVID-19 pandemic: Evidence from international stock markets," Finance Research Letters, Elsevier, vol. 48(C).
    674. Xie Haibin & Zhou Mo & Hu Yi & Yu Mei, 2014. "Forecasting the Crude Oil Price with Extreme Values," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 193-205, June.
    675. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    676. Xu, Yahua & Bouri, Elie & Saeed, Tareq & Wen, Zhuzhu, 2020. "Intraday return predictability: Evidence from commodity ETFs and their related volatility indices," Resources Policy, Elsevier, vol. 69(C).
    677. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    678. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    679. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
    680. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    681. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    682. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    683. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).
    684. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    685. Feng He & Libo Yin, 2021. "Shocks to the equity capital ratio of financial intermediaries and the predictability of stock return volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 945-962, September.
    686. Stig V. Møller & Jesper Rangvid, 2012. "End-of-the-year economic growth and time-varying expected returns," CREATES Research Papers 2012-42, Department of Economics and Business Economics, Aarhus University.
    687. Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).
    688. Fang, Yue & Luo, Deming & Yao, Zhongwei, 2024. "Belief dispersion in the Chinese stock market and fund flows," Journal of Banking & Finance, Elsevier, vol. 166(C).
    689. Bing Han & Gang Li, 2021. "Information Content of Aggregate Implied Volatility Spread," Management Science, INFORMS, vol. 67(2), pages 1249-1269, February.
    690. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    691. Procasky, William J. & Yin, Anwen, 2023. "Identifying the true nature of price discovery and cross-market informational flow in the investment grade CDS and equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    692. Kroencke, Tim A., 2022. "Recessions and the stock market," Journal of Monetary Economics, Elsevier, vol. 131(C), pages 61-77.
    693. Li Liu & Zhiyuan Pan & Yudong Wang, 2021. "What can we learn from the return predictability over the business cycle?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 108-131, January.
    694. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    695. Yin, Libo & Feng, Jiabao & Han, Liyan, 2021. "Systemic risk in international stock markets: Role of the oil market," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 592-619.
    696. Haibin Xie & Shouyang Wang, 2018. "Timing the market: the economic value of price extremes," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-24, December.
    697. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
    698. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
    699. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    700. Zeng, Qing & Tang, Yusui & Yang, Hua & Zhang, Xi, 2024. "Stock market volatility and economic policy uncertainty: New insight into a dynamic threshold mixed-frequency model," Finance Research Letters, Elsevier, vol. 59(C).
    701. Guanhao Feng & Jingyu He, 2019. "Factor Investing: A Bayesian Hierarchical Approach," Papers 1902.01015, arXiv.org, revised Sep 2020.
    702. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    703. Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).
    704. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.
    705. Turtle, H.J. & Wang, Kainan, 2016. "The benefits of improved covariance estimation," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 233-246.
    706. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.

  19. Ravi Jagannathan & Ernst Schaumburg & Guofu Zhou, 2010. "Cross-Sectional Asset Pricing Tests," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 49-74, December.

    Cited by:

    1. Liao Zhu & Sumanta Basu & Robert A. Jarrow & Martin T. Wells, 2018. "High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor Model," Papers 1804.08472, arXiv.org, revised Dec 2021.
    2. Adam Zaremba, 2019. "The Cross Section of Country Equity Returns: A Review of Empirical Literature," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    3. Robert Jarrow, 2016. "Bubbles And Multiple-Factor Asset Pricing Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-19, February.
    4. Thewissen, James & Torsin, Wouter & Boudt, Kris, 2018. "When does the tone of earnings press releases matter?," LIDAM Reprints LFIN 2018001, Université catholique de Louvain, Louvain Finance (LFIN).
    5. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    6. Liao Zhu & Robert A. Jarrow & Martin T. Wells, 2020. "Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model," Papers 2011.04171, arXiv.org, revised Apr 2021.
    7. PAOLA BRIGHI & STEFANO d'ADDONA & ANTONIO CARLO FRANCESCO DELLA BINA, 2013. "The Determinants of Risk Premia on the Italian Stock Market: Empirical Evidence on Common Factors in Asset Pricing Models," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(2), pages 103-133, July.
    8. Liao Zhu, 2021. "The Adaptive Multi-Factor Model and the Financial Market," Papers 2107.14410, arXiv.org, revised Aug 2021.
    9. Skočir, Matevž & Lončarski, Igor, 2018. "Multi-factor asset pricing models: Factor construction choices and the revisit of pricing factors," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 65-80.
    10. Robert Jarrow, 2018. "Asset market equilibrium with liquidity risk," Annals of Finance, Springer, vol. 14(2), pages 253-288, May.
    11. Baek, Seungho & Bilson, John F.O., 2015. "Size and value risk in financial firms," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 295-326.
    12. Hollstein, Fabian & Prokopczuk, Marcel, 2022. "Testing Factor Models in the Cross-Section," Journal of Banking & Finance, Elsevier, vol. 145(C).
    13. Johan Knif & James W. Kolari & Gregory Koutmos & Seppo Pynnönen, 2019. "Measuring the relative return contribution of risk factors," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 263-272, July.
    14. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    15. Robert Jarrow, 2018. "An Equilibrium Capital Asset Pricing Model in Markets with Price Jumps and Price Bubbles," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-33, June.
    16. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    17. Christian Fieberg & Armin Varmaz & Thorsten Poddig, 2016. "Covariances vs. characteristics: what does explain the cross section of the German stock market returns?," Business Research, Springer;German Academic Association for Business Research, vol. 9(1), pages 27-50, April.
    18. Robert Jarrow, 2017. "A Capm With Trading Constraints And Price Bubbles," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-39, December.

  20. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    3. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    4. Bodnar, Olha & Bodnar, Taras & Niklasson, Vilhelm, 2024. "Constructing Bayesian tangency portfolios under short-selling restrictions," Finance Research Letters, Elsevier, vol. 62(PA).
    5. Evan Anderson & Ai-ru (Meg) Cheng, 2022. "Portfolio Choices with Many Big Models," Management Science, INFORMS, vol. 68(1), pages 690-715, January.
    6. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    7. Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Tavakkoli, Hamid Raza & Rezgui, Hichem, 2024. "Does Islamic investing modify portfolio performance? Time-varying optimization strategies for conventional and Shariah energy-ESG-utilities portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 37-57.
    8. Fuertes, Ana-Maria & Zhao, Nan, 2023. "A Bayesian perspective on commodity style integration," Journal of Commodity Markets, Elsevier, vol. 30(C).
    9. Bodnar, Taras & Mazur, Stepan & Nguyen, Hoang, 2022. "Estimation of optimal portfolio compositions for small sampleand singular covariance matrix," Working Papers 2022:15, Örebro University, School of Business.
    10. Kim, Dongwhan & Kang, Kyu Ho, 2021. "Conditional value-at-risk forecasts of an optimal foreign currency portfolio," International Journal of Forecasting, Elsevier, vol. 37(2), pages 838-861.
    11. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    12. Dragon Yongjun Tang, 2014. "Potential losses from incorporating return predictability into portfolio allocation," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 35-45, February.
    13. Massimo Guidolin & Hening Liu, 2013. "Ambiguity Aversion and Under-diversification," Working Papers 483, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    14. Scott Cederburg & Travis L Johnson & Michael S O’Doherty, 2023. "On the Economic Significance of Stock Return Predictability," Review of Finance, European Finance Association, vol. 27(2), pages 619-657.
    15. David Bauder & Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2021. "Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 221-242, February.
    16. Sangwon Suh, 2016. "A Combination Rule for Portfolio Selection with Transaction Costs," International Review of Finance, International Review of Finance Ltd., vol. 16(3), pages 393-420, September.
    17. Taras Bodnar & Vilhelm Niklasson & Erik Thors'en, 2022. "Volatility Sensitive Bayesian Estimation of Portfolio VaR and CVaR," Papers 2205.01444, arXiv.org.
    18. Taras Bodnar & Mathias Lindholm & Vilhelm Niklasson & Erik Thors'en, 2020. "Bayesian Quantile-Based Portfolio Selection," Papers 2012.01819, arXiv.org.
    19. Johannes Bock, 2018. "An updated review of (sub-)optimal diversification models," Papers 1811.08255, arXiv.org.
    20. Veronesi, Pietro & Pástor, Luboš, 2009. "Learning in Financial Markets," CEPR Discussion Papers 7127, C.E.P.R. Discussion Papers.
    21. Fabozzi, Frank J. & Huang, Dashan & Jiang, Fuwei & Wang, Jiexun, 2024. "What difference do new factor models make in portfolio allocation?," Journal of International Money and Finance, Elsevier, vol. 140(C).
    22. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
    23. Marcos Escobar-Anel & Max Speck & Rudi Zagst, 2024. "Bayesian Learning in an Affine GARCH Model with Application to Portfolio Optimization," Mathematics, MDPI, vol. 12(11), pages 1-27, May.
    24. Bodnar, Taras & Mazur, Stepan & Okhrin, Yarema, 2017. "Bayesian estimation of the global minimum variance portfolio," European Journal of Operational Research, Elsevier, vol. 256(1), pages 292-307.
    25. Qiao, W. & Bu, D. & Gibberd, A. & Liao, Y. & Wen, T. & Li, E., 2023. "When “time varying” volatility meets “transaction cost” in portfolio selection," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 220-237.
    26. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2015. "Equally Weighted vs. Long†Run Optimal Portfolios," European Financial Management, European Financial Management Association, vol. 21(4), pages 742-789, September.
    27. Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
    28. Thomas J. Brennan & Andrew W. Lo, 2008. "Impossible Frontiers," NBER Working Papers 14525, National Bureau of Economic Research, Inc.

  21. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.

    Cited by:

    1. Chen, Kuan-Hau & Su, Xuan-Qi & Lin, Li-Feng & Shih, Yi-Cheng, 2021. "Profitability of moving-average technical analysis over the firm life cycle: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    2. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Econometric Institute Research Papers EI2018-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Eun-chong Kim & Han-wook Jeong & Nak-young Lee, 2019. "Global Asset Allocation Strategy Using a Hidden Markov Model," JRFM, MDPI, vol. 12(4), pages 1-15, November.
    4. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    5. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    6. Kai Li & Jun Liu, 2016. "Reversing Momentum: The Optimal Dynamic Momentum Strategy," Research Paper Series 370, Quantitative Finance Research Centre, University of Technology, Sydney.
    7. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    8. Shi Yafeng & Yanlong Shi & Ying Tingting, 2024. "Can technical indicators based on underlying assets help to predict implied volatility index," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 57-74, January.
    9. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "Asymmetric Risk Impacts of Chinese Tourists to Taiwan," Tinbergen Institute Discussion Papers 18-047/III, Tinbergen Institute.
    10. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    11. Hyungjun Park & Min Kyu Sim & Dong Gu Choi, 2019. "An intelligent financial portfolio trading strategy using deep Q-learning," Papers 1907.03665, arXiv.org, revised Nov 2019.
    12. Chen, Xingjiang & Ruan, Xinfeng & Zhang, Wenjun, 2021. "Dynamic portfolio choice and information trading with recursive utility," Economic Modelling, Elsevier, vol. 98(C), pages 154-167.
    13. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
    14. K. J. Hong & S. Satchell, 2013. "Time Series Momentum Trading Strategy and Autocorrelation Amplification," Cambridge Working Papers in Economics 1322, Faculty of Economics, University of Cambridge.
    15. Matheus José Silva de Souza & Danilo Guimarães Franco Ramos & Marina Garcia Pena & Vinicius Amorim Sobreiro & Herbert Kimura, 2018. "Examination of the profitability of technical analysis based on moving average strategies in BRICS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-18, December.
    16. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    17. Ansari Saleh Ahmar, 2019. "Sutte Indicator: an approach to predict the direction of stock market movements," Papers 1903.11642, arXiv.org.
    18. Erdemlioglu, Deniz & Petitjean, Mikael & Vargas, Nicolas, 2021. "Market Instability and Technical Trading at High Frequency: Evidence from NASDAQ Stocks," LIDAM Reprints LFIN 2021016, Université catholique de Louvain, Louvain Finance (LFIN).
    19. Lord Mensah, 2016. "Asset Allocation Brewed Accross African Stock Markets," Proceedings of Economics and Finance Conferences 3205757, International Institute of Social and Economic Sciences.
    20. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    21. Yehong Liu & Guosheng Yin, 2018. "Average Holding Price," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
    22. Noureddine Kouaissah & Amin Hocine, 2021. "Forecasting systemic risk in portfolio selection: The role of technical trading rules," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 708-729, July.
    23. Yufeng Han & Lingfei Kong, 2022. "A trend factor in commodity futures markets: Any economic gains from using information over investment horizons?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 803-822, May.
    24. Massoud Metghalchi & Linda A. Hayes & Farhang Niroomand, 2019. "A technical approach to equity investing in emerging markets," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 389-403, July.
    25. Yao-Tsung Wu & Chien-Hung Liu & Kuo-Hao Lin & Dun-Yao Ke, 2024. "Does media coverage matter for the performance of technical trading strategies? Evidence from Taiwan," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(1), pages 147-166, January.
    26. Keith S. K. Lam & Liang Dong & Bo Yu, 2019. "Value Premium and Technical Analysis: Evidence from the China Stock Market," Economies, MDPI, vol. 7(3), pages 1-21, September.
    27. Gu, Ming & Sun, Minxing & Xiong, Zhitao & Xu, Weike, 2024. "Market volatility and the trend factor," Finance Research Letters, Elsevier, vol. 65(C).
    28. Adrian Zoicas‐Ienciu, 2021. "Evaluating active investing with generic trading reactions," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1018-1036, January.
    29. Amit Bhaya & Eugenius Kaszkurewicz & Leonardo Valente Ferreira, 2024. "A Dynamic Trading Model for Use with a One Step Ahead Optimal Strategy," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1575-1608, April.
    30. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    31. He, Xue-Zhong & Li, Kai, 2015. "Profitability of time series momentum," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 140-157.
    32. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    33. Demir Bektić & Tobias Regele, 2018. "Exploiting uncertainty with market timing in corporate bond markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 79-92, March.
    34. Paskalis Glabadanidis, 2014. "The Market Timing Power of Moving Averages: Evidence from US REITs and REIT Indexes," International Review of Finance, International Review of Finance Ltd., vol. 14(2), pages 161-202, June.
    35. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Market Timing with Moving Averages for Fossil Fuel and Renewable Energy Stocks," Econometric Institute Research Papers EI2018-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    36. Dai, Min & Li, Peifan & Zhang, Jin E., 2010. "A lattice algorithm for pricing moving average barrier options," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 542-554, March.
    37. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    38. Hong, KiHoon & Wu, Eliza, 2016. "The roles of past returns and firm fundamentals in driving US stock price movements," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 62-75.
    39. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2017. "Time series momentum and moving average trading rules," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 405-421, March.
    40. Xue-Zhong He & Kai Li, 2014. "Time Series Momentum and Market Stability," Research Paper Series 341, Quantitative Finance Research Centre, University of Technology, Sydney.
    41. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    42. Carl Chiarella & Xue-Zhong He & Remco C.J. Zwinkels, 2014. "Heterogeneous Expectations in Asset Pricing: Empirical Evidence from the S&P500," Research Paper Series 344, Quantitative Finance Research Centre, University of Technology, Sydney.
    43. Enrico Biffis & Fausto Gozzi & Cecilia Prosdocimi, 2020. "Optimal portfolio choice with path dependent labor income: the infinite horizon case," Papers 2002.00201, arXiv.org.
    44. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    45. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    46. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
    47. K. J. Hong & S. Satchell, 2015. "Time series momentum trading strategy and autocorrelation amplification," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1471-1487, September.
    48. Ahmed Bel Hadj Ayed & Gr'egoire Loeper & Fr'ed'eric Abergel, 2016. "Robustness of mathematical models and technical analysis strategies," Papers 1605.00173, arXiv.org.
    49. Michels, Rouven & Ötting, Marius & Langrock, Roland, 2023. "Bettors’ reaction to match dynamics: Evidence from in-game betting," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1118-1127.
    50. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    51. Stefanescu, Răzvan & Dumitriu, Ramona, 2015. "Buy and sell signals on Bucharest Stock Exchange," MPRA Paper 89014, University Library of Munich, Germany, revised 05 Jan 2016.
    52. Isakov, Dusan & Marti, Didier, 2011. "Technical Analysis with a Long-Term Perspective: Trading Strategies and Market Timing Ability," FSES Working Papers 421, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    53. Paskalis Glabadanidis, 2015. "Market Timing With Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 387-425, September.
    54. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    55. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    56. KiHoon Jimmy Hong & Eliza Wu, 2014. "Can Momentum Factors Be Used to Enhance Accounting Information based Fundamental Analysis in Explaining Stock Price Movements?," Research Paper Series 346, Quantitative Finance Research Centre, University of Technology, Sydney.
    57. Jukka Ilomäki, 2018. "Risk and return of a trend-chasing application in financial markets: an empirical test," Risk Management, Palgrave Macmillan, vol. 20(3), pages 258-272, August.
    58. Paskalis Glabadanidis, 2017. "Timing the Market with a Combination of Moving Averages," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 353-394, September.
    59. Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Market Timing with Moving Averages," Econometric Institute Research Papers EI 2018-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    60. Papailias, Fotis & Thomakos, Dimitrios D., 2015. "An improved moving average technical trading rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 458-469.
    61. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    62. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
    63. Ko, Kuan-Cheng & Lin, Shinn-Juh & Su, Hsiang-Ju & Chang, Hsing-Hua, 2014. "Value investing and technical analysis in Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 14-36.
    64. Metghalchi, Massoud & Chen, Chien-Ping & Hayes, Linda A., 2015. "History of share prices and market efficiency of the Madrid general stock index," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 178-184.
    65. Yufeng Lin & Xiaogang Wang & Yuehua Wu, 2023. "An Adaptive Multiple-Asset Portfolio Strategy with User-Specified Risk Tolerance," Mathematics, MDPI, vol. 11(7), pages 1-35, March.
    66. Samreen Fahim Babar & Zeeshan Yasir, 2021. "Financial Institutions and Chinese Investment: The Review of China Pakistan Economic Corridor (CPEC) Policy," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 4, May - Aug.
    67. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    68. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.
    69. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    70. Jim Kyung-Soo Liew & Ahmad Ajakh, 2020. "Volatility-Adjusted 60/40 versus 100—New Risk Investing Paradigm," JRFM, MDPI, vol. 13(9), pages 1-6, August.
    71. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    72. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 089-115, December.
    73. Scholz, Peter, 2012. "Size matters! How position sizing determines risk and return of technical timing strategies," CPQF Working Paper Series 31, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    74. Ebert, Sebastian & Hilpert, Christian, 2019. "Skewness preference and the popularity of technical analysis," Journal of Banking & Finance, Elsevier, vol. 109(C).
    75. Heng-Chih Chou & Dar-Hsin Chen, 2019. "The use of technical analysis in sale-and-purchase transactions of secondhand ships," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(2), pages 223-240, June.
    76. Panha Heng & Scott J. Niblock, 2014. "Trading with Tigers: A Technical Analysis of Southeast Asian Stock Index Futures," International Economic Journal, Taylor & Francis Journals, vol. 28(4), pages 679-692, December.
    77. Eugenio D’Angelo & Giulio Grimaldi, 2017. "The Effectiveness of the Elliott Waves Theory to Forecast Financial Markets: Evidence from the Currency Market," International Business Research, Canadian Center of Science and Education, vol. 10(6), pages 1-18, June.
    78. Joseph Zhi Bin Ling & Albert K. Tsui & Zhaoyong Zhang, 2021. "Trading Macro-Cycles of Foreign Exchange Markets Using Hybrid Models," Sustainability, MDPI, vol. 13(17), pages 1-20, September.
    79. Liping Wang & Jiawei Li & Lifan Zhao & Zhizhuo Kou & Xiaohan Wang & Xinyi Zhu & Hao Wang & Yanyan Shen & Lei Chen, 2023. "Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey," Papers 2308.04947, arXiv.org.
    80. Ryan Flugum, 2021. "The trend is an analyst's friend: Analyst recommendations and market technicals," The Financial Review, Eastern Finance Association, vol. 56(2), pages 301-330, May.
    81. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
    82. Jin, Xiaoye, 2021. "What do we know about the popularity of technical analysis in foreign exchange markets? A skewness preference perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    83. Xianzhe Chen & Weidong Tian, 2014. "Optimal portfolio choice and consistent performance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 453-474, October.
    84. Hui Zeng & Ben R Marshall & Nhut H Nguyen & Nuttawat Visaltanachoti, 2022. "Are individual stock returns predictable?," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 135-162, February.
    85. Santos, André A.P. & Torrent, Hudson S., 2022. "Markowitz meets technical analysis: Building optimal portfolios by exploiting information in trend-following signals," Finance Research Letters, Elsevier, vol. 49(C).
    86. Hyung-Chul Jo & Hyang-A Park & Soon-Young Kwon & Kyeong-Hee Cho, 2024. "Home Energy Management Systems (HEMSs) with Optimal Energy Management of Home Appliances Using IoT," Energies, MDPI, vol. 17(12), pages 1-15, June.
    87. Afiruddin Tapa* & Mohd Hasimi Yaacob & Ahmad Husni Hamzah & Yean Soh Chuen, 2018. "Trading Performance Analysis: A Comparisons Between the Original MA Crossover and Modified MA Crossover Strategy," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 933-941:6.
    88. Cepoi, Cosmin-Octavian & Anghel, Dan-Gabriel & Pop, Ionuţ Daniel, 2021. "Asymmetries and flight-to-safety effects in the price discovery process of cross-listed stocks," Economic Modelling, Elsevier, vol. 98(C), pages 302-318.
    89. Ansari Saleh Ahmar & Abdul Rahman & Andi Nurani Mangkawani Arifin & Alfatih Abqary Ahmar, 2017. "Predicting movement of stock of “Y” using Sutte Indicator," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1347123-134, January.
    90. Ansari Saleh Ahmar, 2017. "Sutte Indicator: A Technical Indicator in Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 223-226.
    91. Fernandes, Betina & Street, Alexandre & Valladão, Davi & Fernandes, Cristiano, 2016. "An adaptive robust portfolio optimization model with loss constraints based on data-driven polyhedral uncertainty sets," European Journal of Operational Research, Elsevier, vol. 255(3), pages 961-970.
    92. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
    93. Corsaro, Stefania & Kyriakou, Ioannis & Marazzina, Daniele & Marino, Zelda, 2019. "A general framework for pricing Asian options under stochastic volatility on parallel architectures," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1082-1095.
    94. Guohao Tang & Fuwei Jiang & Xinlin Qi & Nan Huang, 2021. "It takes two to tango: Fundamental timing in stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5259-5277, October.
    95. Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).

  22. Kan, Raymond & Zhou, Guofu, 2007. "Optimal Portfolio Choice with Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 621-656, September.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Gabriel Frahm & Tobias Wickern & Christof Wiechers, 2012. "Multiple tests for the performance of different investment strategies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 343-383, July.
    3. Thomas Trier Bjerring & Omri Ross & Alex Weissensteiner, 2017. "Feature selection for portfolio optimization," Annals of Operations Research, Springer, vol. 256(1), pages 21-40, September.
    4. Fletcher, Jonathan, 2011. "Do optimal diversification strategies outperform the 1/N strategy in U.K. stock returns?," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 375-385.
    5. Olessia Caillé & Daria Onori, 2019. "Conditional Risk-Based Portfolio," Finance, Presses universitaires de Grenoble, vol. 40(2), pages 77-117.
    6. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    7. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty: Adaptive Mixing of High- and Low-Frequency Information," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168222, Verein für Socialpolitik / German Economic Association.
    8. Bodnar, Olha & Bodnar, Taras & Niklasson, Vilhelm, 2024. "Constructing Bayesian tangency portfolios under short-selling restrictions," Finance Research Letters, Elsevier, vol. 62(PA).
    9. Evan Anderson & Ai-ru (Meg) Cheng, 2022. "Portfolio Choices with Many Big Models," Management Science, INFORMS, vol. 68(1), pages 690-715, January.
    10. Ding, Wenliang & Shu, Lianjie & Gu, Xinhua, 2023. "A robust Glasso approach to portfolio selection in high dimensions," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 22-37.
    11. Taras Bodnar & Holger Dette & Nestor Parolya & Erik Thors'en, 2019. "Sampling Distributions of Optimal Portfolio Weights and Characteristics in Low and Large Dimensions," Papers 1908.04243, arXiv.org, revised Apr 2023.
    12. Eckhard Platen & Renata Rendek, 2017. "Market Efficiency and the Growth Optimal Portfolio," Research Paper Series 386, Quantitative Finance Research Centre, University of Technology, Sydney.
    13. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    14. Lorenzo Reus & Frank J. Fabozzi, 2021. "Robust Solutions to the Life-Cycle Consumption Problem," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 481-499, February.
    15. Platanakis, Emmanouil & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Horses for courses: Mean-variance for asset allocation and 1/N for stock selection," European Journal of Operational Research, Elsevier, vol. 288(1), pages 302-317.
    16. Dietmar Leisen & Eckhard Platen, 2017. "Investing for the Long Run," Papers 1705.03929, arXiv.org.
    17. Chavez-Bedoya, Luis & Rosales, Francisco, 2021. "Reduction of estimation risk in optimal portfolio choice using redundant constraints," International Review of Financial Analysis, Elsevier, vol. 78(C).
    18. Lara Dalmeyer & Tim Gebbie, 2021. "Geometric insights into robust portfolio construction," Papers 2107.06194, arXiv.org, revised Dec 2024.
    19. Fabio Caccioli & Imre Kondor & Matteo Marsili & Susanne Still, 2014. "$L_p$ regularized portfolio optimization," Papers 1404.4040, arXiv.org.
    20. Jorn Sass & Dorothee Westphal, 2020. "Robust Utility Maximization in a Multivariate Financial Market with Stochastic Drift," Papers 2009.14559, arXiv.org, revised May 2021.
    21. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2017. "Portfolio selection with mental accounts and estimation risk," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 161-186.
    22. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    23. Yan, Lei & Garcia, Philip, 2017. "Portfolio investment: Are commodities useful?," Journal of Commodity Markets, Elsevier, vol. 8(C), pages 43-55.
    24. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    25. Bouaddi, Mohammed & Moutanabbir, Khouzeima, 2023. "Rational distorted beliefs investor; which risk matters?," Finance Research Letters, Elsevier, vol. 51(C).
    26. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Harmful Diversification: Evidence from Alternative Investments," ICMA Centre Discussion Papers in Finance icma-dp2017-09, Henley Business School, University of Reading.
    27. Kan, Raymond & Lassance, Nathan & Wang, Xiaolu, 2023. "The distribution of sample mean-variance portfolio weights," LIDAM Discussion Papers LFIN 2023006, Université catholique de Louvain, Louvain Finance (LFIN).
    28. Klerkx, Rik & Pelsser, Antoon, 2022. "Narrative-based robust stochastic optimization," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 266-277.
    29. Huang, Zhenzhen & Wei, Pengyu & Weng, Chengguo, 2024. "Tail mean-variance portfolio selection with estimation risk," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 218-234.
    30. Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
    31. Castañeda, Pablo & Reus, Lorenzo, 2019. "Suboptimal investment behavior and welfare costs: A simulation based approach," Finance Research Letters, Elsevier, vol. 30(C), pages 170-180.
    32. Jonathan Fletcher, 2024. "AN examination of linear factor models in U.K. stock returns in the presence of dynamic trading," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 1121-1147, October.
    33. A. Burak Paç & Mustafa Ç. Pınar, 2018. "On robust portfolio and naïve diversification: mixing ambiguous and unambiguous assets," Annals of Operations Research, Springer, vol. 266(1), pages 223-253, July.
    34. Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
    35. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2022. "Sparsity and stability for minimum-variance portfolios," Risk Management, Palgrave Macmillan, vol. 24(3), pages 214-235, September.
    36. Chavez-Bedoya, Luis & Rosales, Francisco, 2022. "Orthogonal portfolios to assess estimation risk," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 906-937.
    37. Lassance, Nathan, 2022. "Reconciling mean-variance portfolio theory with non-Gaussian returns," European Journal of Operational Research, Elsevier, vol. 297(2), pages 729-740.
    38. Frahm, Gabriel & Memmel, Christoph, 2009. "Dominating estimators for the global minimum variance portfolio," Discussion Paper Series 2: Banking and Financial Studies 2009,01, Deutsche Bundesbank.
    39. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
    40. Lassance, Nathan, 2023. "An analytical shrinkage estimator for linear regression," Statistics & Probability Letters, Elsevier, vol. 194(C).
    41. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    42. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean-Variance Efficient Large Portfolios : A Simple Machine Learning Heuristic Technique based on the Two-Fund Separation Theorem," Post-Print hal-04514343, HAL.
    43. Chavez-Bedoya, Luis, 2024. "Performance of active portfolio managers when the benchmark is not observable," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    44. A. D. Hall & S. E. Satchell & P. J. Spence, 2015. "Evaluating the impact of inequality constraints and parameter uncertainty on optimal portfolio choice," Applied Economics, Taylor & Francis Journals, vol. 47(45), pages 4801-4813, September.
    45. Kourtis, Apostolos & Dotsis, George & Markellos, Raphael N., 2012. "Parameter uncertainty in portfolio selection: Shrinking the inverse covariance matrix," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2522-2531.
    46. Jiang, Julia & Liu, Jun & Tian, Weidong & Zeng, Xudong, 2022. "Portfolio concentration, portfolio inertia, and ambiguous correlation," Journal of Economic Theory, Elsevier, vol. 203(C).
    47. Jiahan Li, 2015. "Sparse and Stable Portfolio Selection With Parameter Uncertainty," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 381-392, July.
    48. Yen, Yu-Min & Yen, Tso-Jung, 2014. "Solving norm constrained portfolio optimization via coordinate-wise descent algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 737-759.
    49. Javed, Farrukh & Mazur, Stepan & Thorsén, Erik, 2021. "Tangency portfolio weights under a skew-normal model in small and large dimensions," Working Papers 2021:13, Örebro University, School of Business.
    50. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    51. Ni, Xuanming & Zheng, Tiantian & Zhao, Huimin & Zhu, Shushang, 2023. "High-dimensional portfolio optimization based on tree-structured factor model," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    52. Platanakis, Emmanouil & Urquhart, Andrew, 2020. "Should investors include Bitcoin in their portfolios? A portfolio theory approach," The British Accounting Review, Elsevier, vol. 52(4).
    53. Palczewski, Andrzej & Palczewski, Jan, 2014. "Theoretical and empirical estimates of mean–variance portfolio sensitivity," European Journal of Operational Research, Elsevier, vol. 234(2), pages 402-410.
    54. Ruili Sun & Tiefeng Ma & Shuangzhe Liu, 2018. "A Stein-type shrinkage estimator of the covariance matrix for portfolio selections," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(8), pages 931-952, November.
    55. Yonghe Lu & Yanrong Yang & Terry Zhang, 2024. "Double Descent in Portfolio Optimization: Dance between Theoretical Sharpe Ratio and Estimation Accuracy," Papers 2411.18830, arXiv.org.
    56. Ekaterina Seregina, 2020. "A Basket Half Full: Sparse Portfolios," Papers 2011.04278, arXiv.org, revised Apr 2021.
    57. Dirk Paulsen & Jakob Sohl, 2016. "Noise Fit, Estimation Error and a Sharpe Information Criterion," Papers 1602.06186, arXiv.org, revised Dec 2019.
    58. Fabian Ackermann & Walt Pohl & Karl Schmedders, 2012. "Optimal and Naive Diversification in Currency Markets," Swiss Finance Institute Research Paper Series 12-36, Swiss Finance Institute.
    59. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    60. Fassino, Claudia & Torrente, Maria-Laura & Uberti, Pierpaolo, 2022. "A singular value decomposition based approach to handle ill-conditioning in optimization problems with applications to portfolio theory," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    61. Takuya Kinkawa & Nobuo Shinozaki, 2010. "Dominance of a Class of Stein type Estimators for Optimal Portfolio Weights When the Covariance Matrix is Unknown," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 17(1), pages 19-50, March.
    62. Alles Rodrigues, Alexandre & Casalin, Fabrizio, 2022. "Factor investing in Brazil: Diversifying across factor tilts and allocation strategies," Emerging Markets Review, Elsevier, vol. 52(C).
    63. Chulwoo Han, 2020. "How much should portfolios shrink?," Financial Management, Financial Management Association International, vol. 49(3), pages 707-740, September.
    64. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    65. Huang, Hung-Hsi & Lin, Shin-Hung & Wang, Ching-Ping & Chiu, Chia-Yung, 2014. "Adjusting MV-efficient portfolio frontier bias for skewed and non-mesokurtic returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 59-83.
    66. Paskalis Glabadanidis & Leon Zolotoy, 2013. "Benchmark replication portfolio strategies," Journal of Asset Management, Palgrave Macmillan, vol. 14(2), pages 95-110, April.
    67. Drin, Svitlana & Mazur, Stepan & Muhinyuza, Stanislas, 2023. "A test on the location of tangency portfolio for small sample size and singular covariance matrix," Working Papers 2023:11, Örebro University, School of Business.
    68. Raymond Kan & Xiaolu Wang & Guofu Zhou, 2022. "Optimal Portfolio Choice with Estimation Risk: No Risk-Free Asset Case," Management Science, INFORMS, vol. 68(3), pages 2047-2068, March.
    69. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    70. Lassance, Nathan & Vrins, Frédéric, 2023. "Portfolio selection: A target-distribution approach," European Journal of Operational Research, Elsevier, vol. 310(1), pages 302-314.
    71. Boynton, Wentworth & Chen, Fang, 2018. "A parametric bootstrap to evaluate portfolio allocation models," Finance Research Letters, Elsevier, vol. 25(C), pages 76-82.
    72. Jonathan Fletcher, 2022. "Exploring the diversification benefits of US international equity closed-end funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 297-320, September.
    73. Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
    74. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    75. Rose D. Baker & Ian G. McHale, 2013. "Optimal Betting Under Parameter Uncertainty: Improving the Kelly Criterion," Decision Analysis, INFORMS, vol. 10(3), pages 189-199, September.
    76. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    77. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    78. Zhenyu Cui & Majeed Simaan, 2021. "The opportunity cost of hedging under incomplete information: Evidence from ETF/Ns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1775-1796, November.
    79. Wang, Christina Dan & Chen, Zhao & Lian, Yimin & Chen, Min, 2022. "Asset selection based on high frequency Sharpe ratio," Journal of Econometrics, Elsevier, vol. 227(1), pages 168-188.
    80. Gabriel Frahm, 2020. "Statistical properties of estimators for the log-optimal portfolio," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 92(1), pages 1-32, August.
    81. Raymond Kan & Xiaolu Wang, 2024. "Optimal Portfolio Choice with Unknown Benchmark Efficiency," Management Science, INFORMS, vol. 70(9), pages 6117-6138, September.
    82. Linda Chamakh & Emmanuel Gobet & Jean-Philippe Lemor, 2021. "Asymptotic analysis of different covariance matrices estimation for minimum variance portfolio," Working Papers hal-03207061, HAL.
    83. Christopher G. Lamoureux & Huacheng Zhang, 2021. "An Empirical Assessment of Characteristics and Optimal Portfolios," Papers 2104.12975, arXiv.org, revised Feb 2024.
    84. Gabriel Frahm, 2015. "A theoretical foundation of portfolio resampling," Theory and Decision, Springer, vol. 79(1), pages 107-132, July.
    85. Bian, Zhicun & Liao, Yin & O’Neill, Michael & Shi, Jing & Zhang, Xueyong, 2020. "Large-scale minimum variance portfolio allocation using double regularization," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    86. Vijaya Krishna Kanaparthi, 2024. "Navigating Uncertainty: Enhancing Markowitz Asset Allocation Strategies through Out-of-Sample Analysis," FinTech, MDPI, vol. 3(1), pages 1-22, February.
    87. Kentaro Imajo & Kentaro Minami & Katsuya Ito & Kei Nakagawa, 2020. "Deep Portfolio Optimization via Distributional Prediction of Residual Factors," Papers 2012.07245, arXiv.org.
    88. Xinyu Huang & Weihao Han & David Newton & Emmanouil Platanakis & Dimitrios Stafylas & Charles Sutcliffe, 2023. "The diversification benefits of cryptocurrency asset categories and estimation risk: pre and post Covid-19," The European Journal of Finance, Taylor & Francis Journals, vol. 29(7), pages 800-825, May.
    89. Fliege, Jörg & Werner, Ralf, 2014. "Robust multiobjective optimization & applications in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 422-433.
    90. James J. Choi & Adriana Z. Robertson, 2018. "What Matters to Individual Investors? Evidence from the Horse’s Mouth," NBER Working Papers 25019, National Bureau of Economic Research, Inc.
    91. Füss, Roland & Miebs, Felix & Trübenbach, Fabian, 2014. "A jackknife-type estimator for portfolio revision," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 14-28.
    92. Mr. Jorge A Chan-Lau, 2017. "Lasso Regressions and Forecasting Models in Applied Stress Testing," IMF Working Papers 2017/108, International Monetary Fund.
    93. David Bauder & Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2021. "Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 221-242, February.
    94. Gabriele Torri & Rosella Giacometti & Sandra Paterlini, 2019. "Sparse precision matrices for minimum variance portfolios," Computational Management Science, Springer, vol. 16(3), pages 375-400, July.
    95. Bai, Zhidong & Liu, Huixia & Wong, Wing-Keung, 2016. "Making Markowitz's Portfolio Optimization Theory Practically Useful," MPRA Paper 74360, University Library of Munich, Germany.
    96. Francesco Ravazzolo & Marco J. Lombardi, 2012. "Oil price density forecasts: Exploring the linkages with stock markets," Working Papers No 3/2012, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    97. Ding, Yi & Li, Yingying & Zheng, Xinghua, 2021. "High dimensional minimum variance portfolio estimation under statistical factor models," Journal of Econometrics, Elsevier, vol. 222(1), pages 502-515.
    98. Jaydip Sen & Sidra Mehtab, 2021. "Optimum Risk Portfolio and Eigen Portfolio: A Comparative Analysis Using Selected Stocks from the Indian Stock Market," Papers 2107.11371, arXiv.org.
    99. Behr, Patrick & Guettler, Andre & Truebenbach, Fabian, 2012. "Using industry momentum to improve portfolio performance," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1414-1423.
    100. Schotman, Peter C & Lutgens, Frank, 2007. "Robust Portfolio Optimisation with Multiple Experts," CEPR Discussion Papers 6161, C.E.P.R. Discussion Papers.
    101. Ban Kawas & Aurelie Thiele, 2017. "Log-robust portfolio management with parameter ambiguity," Computational Management Science, Springer, vol. 14(2), pages 229-256, April.
    102. Sangwon Suh, 2016. "A Combination Rule for Portfolio Selection with Transaction Costs," International Review of Finance, International Review of Finance Ltd., vol. 16(3), pages 393-420, September.
    103. Frank Fabozzi & Dashan Huang & Guofu Zhou, 2010. "Robust portfolios: contributions from operations research and finance," Annals of Operations Research, Springer, vol. 176(1), pages 191-220, April.
    104. Allen, D. & Lizieri, C. & Satchell, S., 2012. "Mean-Variance versus 1/N: What if we can forecast? (Updated 22nd December 2013)," Cambridge Working Papers in Economics 1244, Faculty of Economics, University of Cambridge.
    105. Svetlana Bender & James J. Choi & Danielle Dyson & Adriana Z. Robertson, 2020. "Millionaires Speak: What Drives Their Personal Investment Decisions?," NBER Working Papers 27969, National Bureau of Economic Research, Inc.
    106. Paskaramoorthy, Andrew & Woolway, Matthew, 2022. "An Empirical Evaluation of Sensitivity Bounds for Mean-Variance Portfolio Optimisation," Finance Research Letters, Elsevier, vol. 44(C).
    107. Petukhina, Alla & Klochkov, Yegor & Härdle, Wolfgang Karl & Zhivotovskiy, Nikita, 2024. "Robustifying Markowitz," Journal of Econometrics, Elsevier, vol. 239(2).
    108. Lan, Wei & Wang, Hansheng & Tsai, Chih-Ling, 2012. "A Bayesian information criterion for portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 88-99, January.
    109. Tu, Xueyong & Li, Bin, 2024. "Robust portfolio selection with smart return prediction," Economic Modelling, Elsevier, vol. 135(C).
    110. Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.
    111. Yuki Shigeta, 2017. "Portfolio selections under mean-variance preference with multiple priors for means and variances," Annals of Finance, Springer, vol. 13(1), pages 97-124, February.
    112. Leung, Pui-Lam & Ng, Hon-Yip & Wong, Wing-Keung, 2012. "An improved estimation to make Markowitz’s portfolio optimization theory users friendly and estimation accurate with application on the US stock market investment," European Journal of Operational Research, Elsevier, vol. 222(1), pages 85-95.
    113. Sang Il Lee, 2020. "Deeply Equal-Weighted Subset Portfolios," Papers 2006.14402, arXiv.org.
    114. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2020. "Company classification using machine learning," Papers 2004.01496, arXiv.org, revised May 2020.
    115. David Bauder & Taras Bodnar & Stepan Mazur & Yarema Okhrin, 2018. "Bayesian Inference For The Tangent Portfolio," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-27, December.
    116. David Stefanovits & Urs Schubiger & Mario V. Wüthrich, 2014. "Model Risk in Portfolio Optimization," Risks, MDPI, vol. 2(3), pages 1-34, August.
    117. Fletcher, Jonathan, 2021. "International equity U.S. mutual funds and diversification benefits," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 246-257.
    118. Kircher, Felix & Rösch, Daniel, 2021. "A shrinkage approach for Sharpe ratio optimal portfolios with estimation risks," Journal of Banking & Finance, Elsevier, vol. 133(C).
    119. Hwang, Inchang & Xu, Simon & In, Francis, 2018. "Naive versus optimal diversification: Tail risk and performance," European Journal of Operational Research, Elsevier, vol. 265(1), pages 372-388.
    120. Hyung, Namwon & de Vries, Casper G., 2012. "Simulating and calibrating diversification against black swans," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1162-1175.
    121. Wolfgang Karl Härdle & David Kuo Chuen Lee & Sergey Nasekin & Alla Petukhina, 2018. "Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(1), pages 49-63, January.
    122. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Sparsity and Stability for Minimum-Variance Portfolios," Papers 1910.11840, arXiv.org.
    123. Hao Liu & Winfried Pohlmeier, 2013. "Risk Preferences and Estimation Risk in Portfolio Choice," Working Paper series 47_13, Rimini Centre for Economic Analysis.
    124. Lim Hao Shen Keith, 2024. "Covariance Matrix Analysis for Optimal Portfolio Selection," Papers 2407.08748, arXiv.org.
    125. Cheng Yan & Ji Yan, 2021. "Optimal and naive diversification in an emerging market: Evidence from China's A‐shares market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3740-3758, July.
    126. Matteo Del Vigna, 2011. "Ambiguity made easier," Working Papers - Mathematical Economics 2011-07, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    127. Yoontae Hwang & Stefan Zohren & Yongjae Lee, 2024. "Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management," Papers 2407.13751, arXiv.org.
    128. Chiang, I-Hsuan Ethan, 2015. "Modern portfolio management with conditioning information," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 114-134.
    129. Kourtis, Apostolos, 2014. "On the distribution and estimation of trading costs," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 104-117.
    130. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper series 66_13, Rimini Centre for Economic Analysis.
    131. Hiraki, Kazuhiro & Sun, Chuanping, 2022. "A toolkit for exploiting contemporaneous stock correlations," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 99-124.
    132. Bodnar, Taras & Mazur, Stepan & Podgórski, Krzysztof, 2016. "Singular inverse Wishart distribution and its application to portfolio theory," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 314-326.
    133. Mynbayeva, Elmira & Lamb, John D. & Zhao, Yuan, 2022. "Why estimation alone causes Markowitz portfolio selection to fail and what we might do about it," European Journal of Operational Research, Elsevier, vol. 301(2), pages 694-707.
    134. Schanbacher Peter, 2015. "Averaging Across Asset Allocation Models," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(1), pages 61-81, February.
    135. Riccardo Lucchetti & Mihaela Nicolau & Giulio Palomba & Luca Riccetti, 2022. "Reconciling TEV and VaR in Active Portfolio Management: A New Frontier," Working Papers 461, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    136. Johannes Bock, 2018. "An updated review of (sub-)optimal diversification models," Papers 1811.08255, arXiv.org.
    137. Wu, Yunlin & Huang, Lei & Jiang, Hui, 2023. "Optimization of large portfolio allocation for new-energy stocks: Evidence from China," Energy, Elsevier, vol. 285(C).
    138. Li, Xiaoyue & Uysal, A. Sinem & Mulvey, John M., 2022. "Multi-period portfolio optimization using model predictive control with mean-variance and risk parity frameworks," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1158-1176.
    139. Moorman, Theodore, 2014. "An empirical investigation of methods to reduce transaction costs," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 230-246.
    140. Veronesi, Pietro & Pástor, Luboš, 2009. "Learning in Financial Markets," CEPR Discussion Papers 7127, C.E.P.R. Discussion Papers.
    141. Caner, Mehmet & Medeiros, Marcelo & Vasconcelos, Gabriel F.R., 2023. "Sharpe Ratio analysis in high dimensions: Residual-based nodewise regression in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 393-417.
    142. Bodnar Taras & Schmid Wolfgang, 2009. "Estimation of optimal portfolio compositions for Gaussian returns," Statistics & Risk Modeling, De Gruyter, vol. 26(3), pages 179-201, April.
    143. Jarrod Wilcox & Frank Fabozzi, 2009. "A Discretionary Wealth Approach to Investment Policy," Yale School of Management Working Papers amz2434, Yale School of Management.
    144. Fabozzi, Frank J. & Huang, Dashan & Jiang, Fuwei & Wang, Jiexun, 2024. "What difference do new factor models make in portfolio allocation?," Journal of International Money and Finance, Elsevier, vol. 140(C).
    145. Zhang, Jinqing & Jin, Zeyu & An, Yunbi, 2017. "Dynamic portfolio optimization with ambiguity aversion," Journal of Banking & Finance, Elsevier, vol. 79(C), pages 95-109.
    146. Andrew Paskaramoorthy & Tim Gebbie & Terence van Zyl, 2021. "The efficient frontiers of mean-variance portfolio rules under distribution misspecification," Papers 2106.10491, arXiv.org, revised Jul 2021.
    147. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    148. Platanakis, Emmanouil & Urquhart, Andrew, 2019. "Portfolio management with cryptocurrencies: The role of estimation risk," Economics Letters, Elsevier, vol. 177(C), pages 76-80.
    149. N'Golo Kone, 2021. "Efficient mean-variance portfolio selection by double regularization," Working Paper 1453, Economics Department, Queen's University.
    150. Michael Senescall & Rand Kwong Yew Low, 2024. "Quantitative Portfolio Management: Review and Outlook," Mathematics, MDPI, vol. 12(18), pages 1-25, September.
    151. Wan-Yi Chiu, 2024. "Portfolio Selection with Hierarchical Isomorphic Risk Aversion," Mathematics, MDPI, vol. 12(21), pages 1-22, October.
    152. Bai, Zhidong & Li, Hua & Wong, Wing-Keung, 2013. "The best estimation for high-dimensional Markowitz mean-variance optimization," MPRA Paper 43862, University Library of Munich, Germany.
    153. Zhen, Fang & Chen, Jingnan, 2022. "A closed-form mean–variance–skewness portfolio strategy," Finance Research Letters, Elsevier, vol. 47(PB).
    154. Maller, Ross & Roberts, Steven & Tourky, Rabee, 2016. "The large-sample distribution of the maximum Sharpe ratio with and without short sales," Journal of Econometrics, Elsevier, vol. 194(1), pages 138-152.
    155. Lassance, Nathan & Vanderveken, Rodolphe & Vrins, Frédéric, 2022. "On the optimal combination of naive and mean-variance portfolio strategies," LIDAM Discussion Papers LFIN 2022006, Université catholique de Louvain, Louvain Finance (LFIN).
    156. Yarema Okhrin & Wolfgang Schmid, 2007. "Comparison of different estimation techniques for portfolio selection," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(2), pages 109-127, August.
    157. Fabio Caccioli & Imre Kondor & Matteo Marsili & Susanne Still, 2016. "Liquidity Risk And Instabilities In Portfolio Optimization," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(05), pages 1-28, August.
    158. Chao Zhang & Zihao Zhang & Mihai Cucuringu & Stefan Zohren, 2021. "A Universal End-to-End Approach to Portfolio Optimization via Deep Learning," Papers 2111.09170, arXiv.org.
    159. Owadally, Iqbal & Landsman, Zinoviy, 2013. "A characterization of optimal portfolios under the tail mean–variance criterion," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 213-221.
    160. Matthias M. M. Buehlmaier & Kit Pong Wong, 2020. "Should investors join the index revolution? Evidence from around the world," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 192-218, May.
    161. Jonathan Fletcher & Elizabeth Littlejohn & Andrew Marshall, 2023. "Exploring the performance of US international bond mutual funds," The Financial Review, Eastern Finance Association, vol. 58(4), pages 765-782, November.
    162. Iwanicz-Drozdowska Małgorzata & Rogowicz Karol & Smaga Paweł, 2023. "Market-moving events and their role in portfolio optimization of generations X, Y, and Z," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(4), pages 371-397, December.
    163. Andrew Grant & Oh Kang Kwon & Steve Satchell, 2024. "Properties of risk aversion estimated from portfolio weights," Journal of Asset Management, Palgrave Macmillan, vol. 25(5), pages 427-444, September.
    164. Hoevenaars, Roy P.M.M. & Molenaar, Roderick D.J. & Schotman, Peter C. & Steenkamp, Tom B.M., 2008. "Strategic asset allocation with liabilities: Beyond stocks and bonds," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2939-2970, September.
    165. Chiaki Hara & Toshiki Honda, 2014. "Asset Demand and Ambiguity Aversion," KIER Working Papers 911, Kyoto University, Institute of Economic Research.
    166. Olivier Ledoit & Michael Wolf, 2014. "Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks," ECON - Working Papers 137, Department of Economics - University of Zurich, revised Feb 2017.
    167. Junhyeong Lee & Inwoo Tae & Yongjae Lee, 2024. "Anatomy of Machines for Markowitz: Decision-Focused Learning for Mean-Variance Portfolio Optimization," Papers 2409.09684, arXiv.org.
    168. Erdemlioglu, Deniz & Joliet, Robert, 2019. "Long-term asset allocation, risk tolerance and market sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 1-19.
    169. Kan, Raymond & Wang, Xiaolu & Zheng, Xinghua, 2024. "In-sample and out-of-sample Sharpe ratios of multi-factor asset pricing models," Journal of Financial Economics, Elsevier, vol. 155(C).
    170. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
    171. Bodnar, Taras & Mazur, Stepan & Okhrin, Yarema, 2017. "Bayesian estimation of the global minimum variance portfolio," European Journal of Operational Research, Elsevier, vol. 256(1), pages 292-307.
    172. Hongseon Kim & Soonbong Lee & Seung Bum Soh & Seongmoon Kim, 2022. "Improving portfolio investment performance with distance‐based portfolio‐combining algorithms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(4), pages 941-959, December.
    173. Joo, Young C. & Park, Sung Y., 2021. "Optimal portfolio selection using a simple double-shrinkage selection rule," Finance Research Letters, Elsevier, vol. 43(C).
    174. Xiao, Helu & Ren, Tiantian & Zhou, Zhongbao & Liu, Wenbin, 2021. "Parameter uncertainty in estimation of portfolio efficiency: Evidence from an interval diversification-consistent DEA approach," Omega, Elsevier, vol. 103(C).
    175. Bodnar, Taras & Okhrin, Yarema, 2008. "Properties of the singular, inverse and generalized inverse partitioned Wishart distributions," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2389-2405, November.
    176. Härdle, Wolfgang & Klochkov, Yegor & Petukhina, Alla & Zhivotovskiy, Nikita, 2021. "Robustifying Markowitz," IRTG 1792 Discussion Papers 2021-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    177. Peter Nystrup & Stephen Boyd & Erik Lindström & Henrik Madsen, 2019. "Multi-period portfolio selection with drawdown control," Annals of Operations Research, Springer, vol. 282(1), pages 245-271, November.
    178. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    179. Vasyl Golosnoy, 2010. "No-transaction bounds and estimation risk," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 487-493.
    180. Katrin Schöttle & Ralf Werner & Rudi Zagst, 2010. "Comparison and robustification of Bayes and Black-Litterman models," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(3), pages 453-475, June.
    181. Alexandros Kostakis & Nikolaos Panigirtzoglou & George Skiadopoulos, 2011. "Market Timing with Option-Implied Distributions: A Forward-Looking Approach," Management Science, INFORMS, vol. 57(7), pages 1231-1249, July.
    182. Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
    183. Han, Chulwoo, 2020. "A nonparametric approach to portfolio shrinkage," Journal of Banking & Finance, Elsevier, vol. 120(C).
    184. Francisco Rubio & Xavier Mestre & Daniel P. Palomar, 2011. "Performance analysis and optimal selection of large mean-variance portfolios under estimation risk," Papers 1110.3460, arXiv.org.
    185. Sergio Ortobelli & Noureddine Kouaissah & Tomáš Tichý, 2019. "On the use of conditional expectation in portfolio selection problems," Annals of Operations Research, Springer, vol. 274(1), pages 501-530, March.
    186. Yan, Cheng & Zhang, Huazhu, 2017. "Mean-variance versus naïve diversification: The role of mispricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 61-81.
    187. Chakrabarti, Deepayan, 2021. "Parameter-free robust optimization for the maximum-Sharpe portfolio problem," European Journal of Operational Research, Elsevier, vol. 293(1), pages 388-399.
    188. Branger, Nicole & Lučivjanská, Katarína & Weissensteiner, Alex, 2019. "Optimal granularity for portfolio choice," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 125-146.
    189. Gabriel Frahm & Christoph Memmel, 2010. "Dominating Estimators for Minimum-Variance Portfolios," Post-Print hal-00741629, HAL.
    190. Giovanni Bonaccolto & Sandra Paterlini, 2020. "Developing new portfolio strategies by aggregation," Annals of Operations Research, Springer, vol. 292(2), pages 933-971, September.
    191. Zhu, Bo & Zhang, Tianlun, 2021. "Long-term wealth growth portfolio allocation under parameter uncertainty: A non-conservative robust approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    192. Istvan Varga-Haszonits & Fabio Caccioli & Imre Kondor, 2016. "Replica approach to mean-variance portfolio optimization," Papers 1606.08679, arXiv.org.
    193. Golosnoy, Vasyl & Okhrin, Yarema, 2008. "General uncertainty in portfolio selection: A case-based decision approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 718-734, September.
    194. Platanakis, Emmanouil & Sutcliffe, Charles & Urquhart, Andrew, 2018. "Optimal vs naïve diversification in cryptocurrencies," Economics Letters, Elsevier, vol. 171(C), pages 93-96.
    195. Miguel, Victor de & Nogales, Francisco J., 2013. "Parameter uncertainty in multiperiod portfolio optimization with transaction costs," DES - Working Papers. Statistics and Econometrics. WS ws132119, Universidad Carlos III de Madrid. Departamento de Estadística.
    196. Max Heide & Benjamin R. Auer & Frank Schuhmacher, 2025. "Optimal Versus Naive Diversification in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(1), pages 3-22, January.
    197. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J., 2013. "Size matters: Optimal calibration of shrinkage estimators for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3018-3034.
    198. Serge Darolles & Christian Gouriéroux & Emmanuelle Jay, 2012. "Robust Portfolio Allocation with Systematic Risk Contribution Restrictions," Working Papers 2012-35, Center for Research in Economics and Statistics.
    199. Wickern, Tobias, 2011. "Confidence in prior knowledge: Calibration and impact on portfolio performance," Discussion Papers in Econometrics and Statistics 7/11, University of Cologne, Institute of Econometrics and Statistics.
    200. Thomas J. Brennan & Andrew W. Lo, 2008. "Impossible Frontiers," NBER Working Papers 14525, National Bureau of Economic Research, Inc.
    201. Raymond Kan & Daniel R. Smith, 2008. "The Distribution of the Sample Minimum-Variance Frontier," Management Science, INFORMS, vol. 54(7), pages 1364-1380, July.
    202. Bäuerle, Nicole & Mahayni, Antje, 2024. "Optimal investment in ambiguous financial markets with learning," European Journal of Operational Research, Elsevier, vol. 315(1), pages 393-410.
    203. Dilip Patro & Louis R. Piccotti & Yangru Wu, 2017. "Exploiting Closed-End Fund Discounts: A Systematic Examination Of Alphas," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 40(2), pages 223-248, June.
    204. Kourtis, Apostolos, 2016. "The Sharpe ratio of estimated efficient portfolios," Finance Research Letters, Elsevier, vol. 17(C), pages 72-78.
    205. Jonathan Fletcher, 2009. "Risk Reduction and Mean‐Variance Analysis: An Empirical Investigation," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(7‐8), pages 951-971, September.
    206. Breuer, Wolfgang & Gürtler, Marc, 2010. "Implied rates of return, the discount rate effect, and market risk premia," Working Papers IF33V3, Technische Universität Braunschweig, Institute of Finance.
    207. Hubáček, Ondřej & Šír, Gustav, 2023. "Beating the market with a bad predictive model," International Journal of Forecasting, Elsevier, vol. 39(2), pages 691-719.
    208. Varga-Haszonits, Istvan & Caccioli, Fabio & Kondor, Imre, 2016. "Replica approach to mean-variance portfolio optimization," LSE Research Online Documents on Economics 68955, London School of Economics and Political Science, LSE Library.
    209. Claußen, Arndt & Rösch, Daniel & Schmelzle, Martin, 2019. "Hedging parameter risk," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 111-121.
    210. Bodnar, Taras & Mazur, Stepan & Muhinyuza, Stanislas & Parolya, Nestor, 2017. "On the product of a singular Wishart matrix and a singular Gaussian vector in high dimensions," Working Papers 2017:7, Örebro University, School of Business.
    211. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    212. Wolfgang Karl Hardle & Yegor Klochkov & Alla Petukhina & Nikita Zhivotovskiy, 2022. "Robustifying Markowitz," Papers 2212.13996, arXiv.org.
    213. Zhou, Zhongbao & Xiao, Helu & Jin, Qianying & Liu, Wenbin, 2018. "DEA frontier improvement and portfolio rebalancing: An application of China mutual funds on considering sustainability information disclosure," European Journal of Operational Research, Elsevier, vol. 269(1), pages 111-131.
    214. Frahm, Gabriel, 2010. "An analytical investigation of estimators for expected asset returns from the perspective of optimal asset allocation," Discussion Papers in Econometrics and Statistics 1/10, University of Cologne, Institute of Econometrics and Statistics.
    215. Kazak, Ekaterina & Pohlmeier, Winfried, 2019. "Testing out-of-sample portfolio performance," International Journal of Forecasting, Elsevier, vol. 35(2), pages 540-554.
    216. Jun Jiang, 2013. "Application of Modern Portfolio Theory In The Case Of Thai Equity Market," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 1(2), pages 33-42.
    217. Roberto Savona & Cesare Orsini, 2019. "Taking the right course navigating the ERC universe," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 157-174, May.
    218. Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, vol. 25(4), pages 760-772, October.
    219. Irina Murtazashvili & Nadia Vozlyublennaia, 2013. "Diversification Strategies: Do Limited Data Constrain Investors?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 36(2), pages 215-232, June.
    220. Michael Christensen & Michael Vangsgaard Christensen & Ken Gamskjaer, 2015. "Delegated portfolio management and optimal allocation of portfolio managers," Applied Economics, Taylor & Francis Journals, vol. 47(21), pages 2142-2153, May.
    221. David Allen & Stephen Satchell & Colin Lizieri, 2024. "Quantifying the non-Gaussian gain," Journal of Asset Management, Palgrave Macmillan, vol. 25(1), pages 1-18, February.
    222. Lassance, Nathan, 2021. "Maximizing the Out-of-Sample Sharpe Ratio," LIDAM Discussion Papers LFIN 2021013, Université catholique de Louvain, Louvain Finance (LFIN).
    223. Turtle, H.J. & Wang, Kainan, 2016. "The benefits of improved covariance estimation," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 233-246.
    224. John R. Birge, 2023. "Uses of Sub-sample Estimates to Reduce Errors in Stochastic Optimization Models," Papers 2310.07052, arXiv.org, revised Jan 2025.

  23. Shanken, Jay & Zhou, Guofu, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," Journal of Financial Economics, Elsevier, vol. 84(1), pages 40-86, April.
    See citations under working paper version above.
  24. Pin-Huang Chou & Guofu Zhou, 2006. "Using Bootstrap to Test Portfolio Efficiency," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 217-249, November.

    Cited by:

    1. Geoffroy Enjolras & Robert Kast & Patrick Sentis, 2009. "Diversification in Area-Yield Crop Insurance : The Multi Linear Additive Model," Working Papers 09-15, LAMETA, Universtiy of Montpellier, revised Nov 2009.
    2. Gurgul, Henryk & Lach, Łukasz, 2010. "International trade and economic growth in the Polish economy," MPRA Paper 52286, University Library of Munich, Germany.
    3. Groenewold, Nicolaas & Fraser, Patricia, 2001. "Tests of asset-pricing models: how important is the iid-normal assumption?," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 427-449, September.
    4. Gurgul, Henryk & Lach, Łukasz, 2011. "The role of coal consumption in the economic growth of the Polish economy in transition," MPRA Paper 52235, University Library of Munich, Germany, revised 2011.
    5. Sermin Gungor & Richard Luger, 2014. "Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings," Staff Working Papers 14-51, Bank of Canada.
    6. José Manuel Cueto & Aurea Grané & Ignacio Cascos, 2021. "How to Explain the Cross-Section of Equity Returns through Common Principal Components," Mathematics, MDPI, vol. 9(9), pages 1-22, April.
    7. Yu, Lu & Li, Yanglin, 2023. "Testing factor models when asset bubbles occur: A time-varying perspective," Economic Modelling, Elsevier, vol. 124(C).
    8. Lach, Łukasz, 2010. "Application of bootstrap methods in investigation of size of the Granger causality test for integrated VAR systems," MPRA Paper 52285, University Library of Munich, Germany.
    9. Cueto, José Manuel, 2021. "How to explain the cross-section of equity returns through Common Principal Components," DES - Working Papers. Statistics and Econometrics. WS 32258, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Robert Kast, 2011. "Managing financial risks due to natural catastrophes," Working Papers hal-00610241, HAL.
    11. Gurgul, Henryk & Lach, Łukasz & Mestel, Roland, 2012. "The relationship between budgetary expenditure and economic growth in Poland," MPRA Paper 52304, University Library of Munich, Germany.
    12. Fletcher, Jonathan, 2018. "Betas V characteristics: Do stock characteristics enhance the investment opportunity set in U.K. stock returns?," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 114-129.
    13. Gurgul, Henryk & Lach, Łukasz, 2011. "Causality analysis between public expenditure and economic growth of Polish economy in last decade," MPRA Paper 52281, University Library of Munich, Germany.
    14. Majumder, Debasish, 2014. "Asset pricing for inefficient markets: Evidence from China and India," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 282-291.
    15. Manuel Galea & David Cademartori & Roberto Curci & Alonso Molina, 2020. "Robust Inference in the Capital Asset Pricing Model Using the Multivariate t -distribution," JRFM, MDPI, vol. 13(6), pages 1-22, June.

  25. Raymond Kan & Guofu Zhou, 2006. "A New Variance Bound on the Stochastic Discount Factor," The Journal of Business, University of Chicago Press, vol. 79(2), pages 941-962, March.

    Cited by:

    1. Raymond Kan & Cesare Robotti, 2016. "The Exact Distribution of the Hansen–Jagannathan Bound," Management Science, INFORMS, vol. 62(7), pages 1915-1943, July.
    2. Glode, Vincent, 2011. "Why mutual funds "underperform"," Journal of Financial Economics, Elsevier, vol. 99(3), pages 546-559, March.
    3. Bakshi, Gurdip & Chabi-Yo, Fousseni, 2012. "Variance bounds on the permanent and transitory components of stochastic discount factors," Journal of Financial Economics, Elsevier, vol. 105(1), pages 191-208.
    4. Bakshi, Gurdip & Chabi-Yo, Fousseni, 2011. "Variance Bounds on the Permanent and Transitory Components of Stochastic Discount Factors," Working Paper Series 2011-11, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    5. Chrétien, Stéphane, 2012. "Bounds on the autocorrelation of admissible stochastic discount factors," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1943-1962.
    6. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    7. Fousseni Chabi-Yo & René Garcia & Eric Renault, 2005. "The Stochastic Discount Factor: Extending the Volatility Bound and a New Approach to Portfolio Selection with Higher-Order Moments," Staff Working Papers 05-2, Bank of Canada.

  26. Chou, Pin-Huang & Li, Wen-Shen & Zhou, Guofu, 2006. "Portfolio optimization under asset pricing anomalies," Japan and the World Economy, Elsevier, vol. 18(2), pages 121-142, March.

    Cited by:

    1. Fannin, J. Matthew & Hughes, David W. & Keithly, Walter R. & Olatubi, Williams O. & Guo, Jiemin, 2008. "Deepwater energy industry impacts on economic growth and public service provision in Lafourche Parish, Louisiana," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 190-205, September.
    2. Branger, Nicole & Lučivjanská, Katarína & Weissensteiner, Alex, 2019. "Optimal granularity for portfolio choice," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 125-146.

  27. Yongmiao Hong & Jun Tu & Guofu Zhou, 2006. "Asymmetries in Stock Returns: Statistical Tests and Economic Evaluation," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1547-1581, 2007 23.

    Cited by:

    1. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    2. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    3. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
    4. Ying Li & Hossein Kazemi, 2007. "Conditional Properties of Hedge Funds: Evidence from Daily Returns," European Financial Management, European Financial Management Association, vol. 13(2), pages 211-238, March.
    5. Zhichao Zhang & Li Ding & Fan Zhang & Zhuang Zhang, 2015. "Optimal Currency Composition for China's Foreign Reserves: A Copula Approach," The World Economy, Wiley Blackwell, vol. 38(12), pages 1947-1965, December.
    6. Hsu, Chih-Chiang & Yau, Ruey & Wu, Jyun-Yi, 2009. "Asymmetric Exchange Rate Exposure and Industry Characteristics : Evidence from Japanese Data," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 50(1), pages 57-69, June.
    7. Numan Ülkü, 2011. "Modeling Comovement among Emerging Stock Markets: The Case of Budapest and Istanbul," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(3), pages 277-304, July.
    8. Plachel, Lukas, 2019. "A unified model for regularized and robust portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    9. Timothy Falcon Crack & Olivier Ledoit, 2010. "Central limit theorems when data are dependent: addressing the pedagogical gaps," IEW - Working Papers 480, Institute for Empirical Research in Economics - University of Zurich.
    10. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    11. Guidolin, Massimo & Hansen, Erwin & Pedio, Manuela, 2019. "Cross-asset contagion in the financial crisis: A Bayesian time-varying parameter approach," Journal of Financial Markets, Elsevier, vol. 45(C), pages 83-114.
    12. Nguyen, Quynh Nga & Aboura, Sofiane & Chevallier, Julien & Zhang, Lyuyuan & Zhu, Bangzhu, 2020. "Local Gaussian correlations in financial and commodity markets," European Journal of Operational Research, Elsevier, vol. 285(1), pages 306-323.
    13. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    14. Peter Christoffersen & Kris Jacobs & Xisong Jin & Hugues Langlois, 2013. "Dynamic Diversification in Corporate Credit," CREATES Research Papers 2013-46, Department of Economics and Business Economics, Aarhus University.
    15. Marc Joëts, 2013. "Energy price transmissions during extreme movements," Working Papers 2013-28, Department of Research, Ipag Business School.
    16. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2020. "Spillovers and co-movements between precious metals and energy markets: Implications on portfolio management," Resources Policy, Elsevier, vol. 69(C).
    17. Massimo Guidolin & Giovanna Nicodano, 2010. "Ex Post Portfolio Performance with Predictable Skewness and Kurtosis," Carlo Alberto Notebooks 191, Collegio Carlo Alberto.
    18. L. Baele & K. Inghelbrecht, 2006. "Structural versus Temporary Drivers of Country and Industry Risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/413, Ghent University, Faculty of Economics and Business Administration.
    19. Immanuel Seidl, 2012. "Markowitz versus Regime Switching: An Empirical Approach," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 033-043, June.
    20. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.
    21. Westner, Günther & Madlener, Reinhard, 2010. "Investment in New Power Generation under Uncertainty: Benefits of CHP vs Condensing Plants in a Copula-Based Analysis," FCN Working Papers 12/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    22. Gerth, Florian & Temnov, Grigory, 2021. "New Ways of Modeling Loan-to-Income Distributions and their Evolution in Time - A Probability Copula Approach," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 217-236.
    23. Fernando D. Chague, 2013. "Conditional Betas and Investor Uncertainty," Working Papers, Department of Economics 2013_04, University of São Paulo (FEA-USP).
    24. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    25. Dahlquist, Magnus & Tédongap, Roméo & Farago, Adam, 2015. "Asymmetries and Portfolio Choice," CEPR Discussion Papers 10706, C.E.P.R. Discussion Papers.
    26. Nguyen, Duc Khuong & Sousa, Ricardo M. & Uddin, Gazi Salah, 2015. "Testing for asymmetric causality between U.S. equity returns and commodity futures returns," Finance Research Letters, Elsevier, vol. 12(C), pages 38-47.

  28. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.

    Cited by:

    1. Evan Anderson & Ai-ru (Meg) Cheng, 2022. "Portfolio Choices with Many Big Models," Management Science, INFORMS, vol. 68(1), pages 690-715, January.
    2. Taras Bodnar & Holger Dette & Nestor Parolya & Erik Thors'en, 2019. "Sampling Distributions of Optimal Portfolio Weights and Characteristics in Low and Large Dimensions," Papers 1908.04243, arXiv.org, revised Apr 2023.
    3. Andrew F. Siegel & Artemiza Woodgate, 2007. "Performance of Portfolios Optimized with Estimation Error," Management Science, INFORMS, vol. 53(6), pages 1005-1015, June.
    4. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "On the Equivalence of Quadratic Optimization Problems Commonly Used in Portfolio Theory," Papers 1207.1029, arXiv.org, revised Apr 2013.
    5. Meichi Huang & Chih-Chiang Wu, 2015. "Economic benefits and determinants of extreme dependences between REIT and stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 299-327, February.
    6. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Harmful Diversification: Evidence from Alternative Investments," ICMA Centre Discussion Papers in Finance icma-dp2017-09, Henley Business School, University of Reading.
    7. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    8. Kourtis, Apostolos & Dotsis, George & Markellos, Raphael N., 2012. "Parameter uncertainty in portfolio selection: Shrinking the inverse covariance matrix," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2522-2531.
    9. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    10. Penaranda, Francisco, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
    11. Taras Bodnar, 2009. "An exact test on structural changes in the weights of the global minimum variance portfolio," Quantitative Finance, Taylor & Francis Journals, vol. 9(3), pages 363-370.
    12. Weidong Tian & Murray Carlson & David A. Chapman & Ron Kaniel & Hong Yan, 2017. "Specification Error, Estimation Risk, and Conditional Portfolio Rules," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 263-288, June.
    13. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
    14. Dragon Yongjun Tang, 2014. "Potential losses from incorporating return predictability into portfolio allocation," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 35-45, February.
    15. Ghysels, Eric & Pereira, João Pedro, 2008. "Liquidity and conditional portfolio choice: A nonparametric investigation," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 679-699, September.
    16. N. Meade & J. E. Beasley & C. J. Adcock, 2019. "Quantitative portfolio selection: using density forecasting to find consistent portfolios," Papers 1908.08442, arXiv.org, revised Jun 2020.
    17. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
    18. Sangwon Suh, 2016. "A Combination Rule for Portfolio Selection with Transaction Costs," International Review of Finance, International Review of Finance Ltd., vol. 16(3), pages 393-420, September.
    19. Frank Fabozzi & Dashan Huang & Guofu Zhou, 2010. "Robust portfolios: contributions from operations research and finance," Annals of Operations Research, Springer, vol. 176(1), pages 191-220, April.
    20. David Stefanovits & Urs Schubiger & Mario V. Wüthrich, 2014. "Model Risk in Portfolio Optimization," Risks, MDPI, vol. 2(3), pages 1-34, August.
    21. Avramov, Doron & Chordia, Tarun, 2006. "Predicting stock returns," Journal of Financial Economics, Elsevier, vol. 82(2), pages 387-415, November.
    22. Bodnar Taras & Schmid Wolfgang, 2011. "On the exact distribution of the estimated expected utility portfolio weights: Theory and applications," Statistics & Risk Modeling, De Gruyter, vol. 28(4), pages 319-342, December.
    23. Bodnar, Taras & Mazur, Stepan & Podgórski, Krzysztof, 2016. "Singular inverse Wishart distribution and its application to portfolio theory," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 314-326.
    24. Veronesi, Pietro & Pástor, Luboš, 2009. "Learning in Financial Markets," CEPR Discussion Papers 7127, C.E.P.R. Discussion Papers.
    25. Bodnar Taras & Schmid Wolfgang, 2009. "Estimation of optimal portfolio compositions for Gaussian returns," Statistics & Risk Modeling, De Gruyter, vol. 26(3), pages 179-201, April.
    26. Fabozzi, Frank J. & Huang, Dashan & Jiang, Fuwei & Wang, Jiexun, 2024. "What difference do new factor models make in portfolio allocation?," Journal of International Money and Finance, Elsevier, vol. 140(C).
    27. Roskelley, Kenneth D., 2008. "Cromwell's Rule and the Role of the Prior in the Economic Metric: An Application to the Portfolio Allocation Problem," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 227-236, April.
    28. David D Cho, 2011. "Estimation risk in covariance," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 248-259, September.
    29. Owadally, Iqbal & Landsman, Zinoviy, 2013. "A characterization of optimal portfolios under the tail mean–variance criterion," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 213-221.
    30. Yufeng Han, 2010. "On the Economic Value of Return Predictability," Annals of Economics and Finance, Society for AEF, vol. 11(1), pages 1-33, May.
    31. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
    32. Golosnoy, Vasyl & Okhrin, Yarema, 2008. "General uncertainty in portfolio selection: A case-based decision approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 718-734, September.
    33. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    34. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    35. Thomas J. Brennan & Andrew W. Lo, 2008. "Impossible Frontiers," NBER Working Papers 14525, National Bureau of Economic Research, Inc.
    36. Bodnar Taras & Schmid Wolfgang & Zabolotskyy Tara, 2012. "Minimum VaR and minimum CVaR optimal portfolios: Estimators, confidence regions, and tests," Statistics & Risk Modeling, De Gruyter, vol. 29(4), pages 281-314, November.
    37. Zhou, Guofu, 2010. "How much stock return predictability can we expect from an asset pricing model?," Economics Letters, Elsevier, vol. 108(2), pages 184-186, August.
    38. Karlsson, Sune & Mazur, Stepan & Muhinyuza, Stanislas, 2020. "Statistical Inference for the Tangency Portfolio in High Dimension," Working Papers 2020:10, Örebro University, School of Business.

  29. Campbell R. Harvey & Bruno Solnik & Guofu Zhou, 2002. "What Determines Expected International Asset Returns?," Annals of Economics and Finance, Society for AEF, vol. 3(2), pages 249-298, November.
    See citations under working paper version above.
  30. Steve Heston & Guofu Zhou, 2000. "On the Rate of Convergence of Discrete‐Time Contingent Claims," Mathematical Finance, Wiley Blackwell, vol. 10(1), pages 53-75, January.

    Cited by:

    1. Primbs, James A. & Yamada, Yuji, 2006. "A moment computation algorithm for the error in discrete dynamic hedging," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 519-540, February.
    2. San-Lin Chung & Pai-Ta Shih, 2007. "Generalized Cox-Ross-Rubinstein Binomial Models," Management Science, INFORMS, vol. 53(3), pages 508-520, March.
    3. Kyoung-Sook Moon & Hongjoong Kim, 2013. "A multi-dimensional local average lattice method for multi-asset models," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 873-884, May.
    4. Windcliff, H. & Vetzal, K. R. & Forsyth, P. A. & Verma, A. & Coleman, T. F., 2003. "An object-oriented framework for valuing shout options on high-performance computer architectures," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 1133-1161, April.
    5. Khaliq, A.Q.M. & Voss, D.A. & Yousuf, M., 2007. "Pricing exotic options with L-stable Pade schemes," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3438-3461, November.
    6. Chuang-Chang Chang & Jun-Biao Lin & Wei-Che Tsai & Yaw-Huei Wang, 2012. "Using Richardson extrapolation techniques to price American options with alternative stochastic processes," Review of Quantitative Finance and Accounting, Springer, vol. 39(3), pages 383-406, October.
    7. Simona Sanfelici, 2004. "Galerkin infinite element approximation for pricing barrier options and options with discontinuous payoff," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 27(2), pages 125-151, December.
    8. Aricson Cruz & José Carlos Dias, 2020. "Valuing American-style options under the CEV model: an integral representation based method," Review of Derivatives Research, Springer, vol. 23(1), pages 63-83, April.
    9. Raahauge, Peter, 2004. "Higher-Order Finite Element Solutions of Option Prices," Working Papers 2004-5, Copenhagen Business School, Department of Finance.
    10. J. X. Jiang & R. H. Liu & D. Nguyen, 2016. "A Recombining Tree Method For Option Pricing With State-Dependent Switching Rates," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 1-26, March.
    11. Mark Broadie & Jerome B. Detemple, 2004. "ANNIVERSARY ARTICLE: Option Pricing: Valuation Models and Applications," Management Science, INFORMS, vol. 50(9), pages 1145-1177, September.
    12. Chandra Sekhara Rao, S. & Manisha,, 2018. "Numerical solution of generalized Black–Scholes model," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 401-421.
    13. H'el`ene Halconruy, 2021. "The insider problem in the trinomial model: a discrete-time jump process approach," Papers 2106.15208, arXiv.org, revised Sep 2023.
    14. N. Hilber & N. Reich & C. Schwab & C. Winter, 2009. "Numerical methods for Lévy processes," Finance and Stochastics, Springer, vol. 13(4), pages 471-500, September.
    15. Luca Barzanti & Corrado Corradi & Martina Nardon, 2006. "On the efficient application of the repeated Richardson extrapolation technique to option pricing," Working Papers 147, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    16. Dong An & Noah Linden & Jin-Peng Liu & Ashley Montanaro & Changpeng Shao & Jiasu Wang, 2020. "Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance," Papers 2012.06283, arXiv.org, revised Jun 2021.
    17. Yong Shin Kim & Stoyan Stoyanov & Svetlozar Rachev & Frank J. Fabozzi, 2017. "Enhancing Binomial and Trinomial Equity Option Pricing Models," Papers 1712.03566, arXiv.org.
    18. Jean-Christophe Breton & Youssef El-Khatib & Jun Fan & Nicolas Privault, 2021. "A q-binomial extension of the CRR asset pricing model," Papers 2104.10163, arXiv.org, revised Feb 2023.
    19. Mark Broadie & Yusaku Yamamoto, 2003. "Application of the Fast Gauss Transform to Option Pricing," Management Science, INFORMS, vol. 49(8), pages 1071-1088, August.
    20. Kozpınar, Sinem & Uzunca, Murat & Karasözen, Bülent, 2020. "Pricing European and American options under Heston model using discontinuous Galerkin finite elements," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 568-587.
    21. Chung, San-Lin & Shih, Pai-Ta, 2009. "Static hedging and pricing American options," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2140-2149, November.
    22. Chang, Chuang-Chang & Lin, Jun-Biao, 2010. "The valuation of contingent claims using alternative numerical methods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 490-508, December.
    23. Gongqiu Zhang & Lingfei Li, 2019. "Analysis of Markov Chain Approximation for Option Pricing and Hedging: Grid Design and Convergence Behavior," Operations Research, INFORMS, vol. 67(2), pages 407-427, March.
    24. Lee, Kiseop & Xu, Mingxin, 2007. "Parameter estimation from multinomial trees to jump diffusions with k means clustering," MPRA Paper 3307, University Library of Munich, Germany, revised 26 Apr 2007.
    25. Yangang Chen & Justin W. L. Wan, 2019. "Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions," Papers 1909.11532, arXiv.org.
    26. Lo-Bin Chang & Ken Palmer, 2007. "Smooth convergence in the binomial model," Finance and Stochastics, Springer, vol. 11(1), pages 91-105, January.
    27. Evis Këllezi & Nick Webber, 2004. "Valuing Bermudan options when asset returns are Levy processes," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 87-100.
    28. John Armstrong & Andrei Ionescu, 2023. "Gamma Hedging and Rough Paths," Papers 2309.05054, arXiv.org, revised Mar 2024.
    29. Katarzyna Toporek, 2012. "Simple is better. Empirical comparison of American option valuation methods," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 29.
    30. Nicola Bruti Liberati & Eckhard Platen, 2004. "On the Efficiency of Simplified Weak Taylor Schemes for Monte Carlo Simulation in Finance," Research Paper Series 114, Quantitative Finance Research Centre, University of Technology, Sydney.
    31. Hörfelt, Per, 2003. "A probabilistic interpretation of the [theta]-method," Statistics & Probability Letters, Elsevier, vol. 62(2), pages 117-122, April.
    32. Chiu, Chun-Yuan & Dai, Tian-Shyr & Lyuu, Yuh-Dauh, 2015. "Pricing Asian option by the FFT with higher-order error convergence rate under Lévy processes," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 418-437.

  31. Zhou, Guofu, 1999. "Security factors as linear combinations of economic variables," Journal of Financial Markets, Elsevier, vol. 2(4), pages 403-432, November.

    Cited by:

    1. Chou, Pin-Huang & Ho, Po-Hsin & Ko, Kuan-Cheng, 2012. "Do industries matter in explaining stock returns and asset-pricing anomalies?," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 355-370.
    2. Kei-Ichiro Inaba, 2018. "Global Stock Return Comovements: Trends and Determinants," Bank of Japan Working Paper Series 18-E-7, Bank of Japan.
    3. Arshad Hasan & M. Tariq Javed, 2009. "An Empirical Investigation of the Causal Relationship among Monetary Variables and Equity Market Returns," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 14(1), pages 115-137, Jan-Jun.
    4. M. Shabri Abd. Majid & Ahamed Kameel Mydin Meera & Mohd. Azmi Omar & Hassanuddeen Abdul Aziz, 2009. "Dynamic linkages among ASEAN‐5 emerging stock markets," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 4(2), pages 160-184, April.
    5. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    6. Kei-Ichiro Inaba, 2020. "A global look into stock market comovements," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(3), pages 517-555, August.
    7. Charles Mossman & Sergiy Rakhmayil, 2011. "Firm size, book-to-market ratio and the macroeconomic environment: theory and test," Applied Economics, Taylor & Francis Journals, vol. 43(19), pages 2417-2431.

  32. Velu, Raja & Zhou, Guofu, 1999. "Testing multi-beta asset pricing models," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 219-241, September.

    Cited by:

    1. Dufour, Jean-Marie & Beaulieu, Marie-Claude & Khalaf, Lynda, 2003. "Testing mean-variance efficiency in CAPM with possibly non-gaussian errors: an exact simulation-based approach," Discussion Paper Series 1: Economic Studies 2003,01, Deutsche Bundesbank.
    2. Lim, G.C., 2005. "Currency risk in excess equity returns: a multi time-varying beta approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 189-207, July.
    3. Marie Briere & Bastien Drut & Valérie Mignon & Kim Oosterlinck & Ariane Szafarz, 2012. "Is the Market Portfolio Efficient? A New Test of Mean-Variance Efficiency when All Assets Are Risky," Working Papers CEB 12-003, ULB -- Universite Libre de Bruxelles.
    4. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
    5. Marie Brière & Bastien Drut & Valérie Mignon & Kim Oosterlinck & Ariane Szafarz, 2011. "Is the Market Portfolio Efficient? A New Test to Revisit the Roll (1977) versus Levy and Roll (2010) Controversy," Working Papers hal-04140988, HAL.
    6. Zhou, Guofu, 1999. "Security factors as linear combinations of economic variables," Journal of Financial Markets, Elsevier, vol. 2(4), pages 403-432, November.
    7. Baek, Seungho & Bilson, John F.O., 2015. "Size and value risk in financial firms," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 295-326.
    8. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2009. "Finite sample multivariate tests of asset pricing models with coskewness," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2008-2021, April.
    9. Enrique Sentana, 2008. "The Econometrics of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
    10. Horváth, Lajos & Li, Bo & Li, Hemei & Liu, Zhenya, 2020. "Time-varying beta in functional factor models: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    11. Massimo Guidolin & Martin Lozano & Juan Arismendi Zambrano, "undated". "Multifactor Empirical Asset Pricing Under Higher-Order Moment Variations," Economics Department Working Paper Series n304-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    12. Jay Shanken & Guofu Zhou, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," CEMA Working Papers 275, China Economics and Management Academy, Central University of Finance and Economics.
    13. Xiangying Meng & Xianhua Wei & Yinchao Chen, 2019. "Estimation on Risk Factor Loading based on Mixed Vine Copula," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 9(3), pages 1-6.

  33. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-587.
    See citations under working paper version above.
  34. Lamoureux, Christopher G & Zhou, Guofu, 1996. "Temporary Components of Stock Returns: What Do the Data Tell Us?," The Review of Financial Studies, Society for Financial Studies, vol. 9(4), pages 1033-1059.

    Cited by:

    1. Eraker, Bjørn, 2008. "A Bayesian view of temporary components in asset prices," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 503-517, June.
    2. Christopher G. Lamoureux & H. Douglas Witte, 2002. "Empirical Analysis of the Yield Curve: The Information in the Data Viewed through the Window of Cox, Ingersoll, and Ross," Journal of Finance, American Finance Association, vol. 57(3), pages 1479-1520, June.
    3. Celso Brunetti & Jeffrey H. Harris & Shawn Mankad, 2018. "Bank Holdings and Systemic Risk," Finance and Economics Discussion Series 2018-063, Board of Governors of the Federal Reserve System (U.S.).
    4. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.
    5. Andrew Ang & Joseph Chen, 2005. "CAPM Over the Long Run: 1926-2001," NBER Working Papers 11903, National Bureau of Economic Research, Inc.
    6. Malliaropulos, Dimitrios, 1998. "International stock return differentials and real exchange rate changes," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 493-511, June.
    7. Smith, L. Vanessa & Yamagata, Takashi, 2011. "Firm level return–volatility analysis using dynamic panels," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 847-867.
    8. Michael W. Brandt & Qiang Kang, 2002. "On the Relationship Between the Conditional Mean and Volatility of Stock Returns: A Latent VAR Approach," NBER Working Papers 9056, National Bureau of Economic Research, Inc.
    9. Montero, Miquel & Perelló, Josep & Masoliver, Jaume, 2002. "Return or stock price differences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 539-560.
    10. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    11. Estrada, Javier, 2000. "The temporal dimension of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(2), pages 189-204.
    12. Estrada, Javier, 1997. "Random walks and the temporal dimension of risk," DEE - Working Papers. Business Economics. WB 7040, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    13. Borup, Daniel, 2019. "Asset pricing model uncertainty," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 166-189.
    14. Brandt, Michael W. & Kang, Qiang, 2004. "On the relationship between the conditional mean and volatility of stock returns: A latent VAR approach," Journal of Financial Economics, Elsevier, vol. 72(2), pages 217-257, May.
    15. Ågren, Martin, 2005. "Myopic Loss Aversion, the Equity Premium Puzzle, and GARCH," Working Paper Series 2005:11, Uppsala University, Department of Economics.
    16. Boguth, Oliver & Carlson, Murray & Fisher, Adlai & Simutin, Mikhail, 2011. "Conditional risk and performance evaluation: Volatility timing, overconditioning, and new estimates of momentum alphas," Journal of Financial Economics, Elsevier, vol. 102(2), pages 363-389.
    17. Stambaugh, Robert F. & Pástor, Luboš, 2007. "Predictive Systems: Living with Imperfect Predictors," CEPR Discussion Papers 6076, C.E.P.R. Discussion Papers.
    18. Roskelley, Kenneth D., 2008. "Cromwell's Rule and the Role of the Prior in the Economic Metric: An Application to the Portfolio Allocation Problem," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 227-236, April.
    19. L. Vanessa Smith & Takashi Yamagata, 2008. "Firm Level Volatility-Return Analysis using Dynamic Panels," Discussion Papers 08/09, Department of Economics, University of York.
    20. Ogden, Joseph P., 2003. "The calendar structure of risk and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 70(1), pages 29-67, October.
    21. Ľuboš Pástor & Robert F. Stambaugh, 2012. "Are Stocks Really Less Volatile in the Long Run?," Journal of Finance, American Finance Association, vol. 67(2), pages 431-478, April.
    22. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    23. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
    24. Neuhierl, Andreas & Varneskov, Rasmus T., 2021. "Frequency dependent risk," Journal of Financial Economics, Elsevier, vol. 140(2), pages 644-675.
    25. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    26. Gropp, Jeffrey, 2004. "Mean reversion of industry stock returns in the U.S., 1926-1998," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 537-551, September.
    27. Hollifield, Burton & Koop, Gary & Li, Kai, 2003. "A Bayesian analysis of a variance decomposition for stock returns," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 583-601, December.

  35. Zhou, Guofu, 1995. "Small sample rank tests with applications to asset pricing," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 71-93, March.

    Cited by:

    1. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-Fit in Multivariate Regressions with Application to Asset Pricing Models," Cahiers de recherche 07-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    3. Dufour, Jean-Marie & Beaulieu, Marie-Claude & Khalaf, Lynda, 2003. "Testing mean-variance efficiency in CAPM with possibly non-gaussian errors: an exact simulation-based approach," Discussion Paper Series 1: Economic Studies 2003,01, Deutsche Bundesbank.
    4. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models," Cahiers de recherche 2003-08, Universite de Montreal, Departement de sciences economiques.
    5. Bura, Efstathia & Cook, R. Dennis, 2003. "Rank estimation in reduced-rank regression," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 159-176, October.
    6. Ziping Zhao & Daniel P. Palomar, 2018. "Sparse Reduced Rank Regression With Nonconvex Regularization," Papers 1803.07247, arXiv.org.
    7. Scott Gilbert & Petr Zemčík, 2005. "Testing for Latent Factors in Models with Autocorrelation and Heteroskedasticity of Unknown Form," Southern Economic Journal, John Wiley & Sons, vol. 72(1), pages 236-252, July.
    8. Raymond Kan & Guofu Zhou, 1999. "A Critique of the Stochastic Discount Factor Methodology," CEMA Working Papers 12, China Economics and Management Academy, Central University of Finance and Economics.
    9. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2009. "Finite sample multivariate tests of asset pricing models with coskewness," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2008-2021, April.
    10. Jay Shanken & Guofu Zhou, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," CEMA Working Papers 275, China Economics and Management Academy, Central University of Finance and Economics.

  36. Zhou, Guofu, 1994. "Analytical GMM Tests: Asset Pricing with Time-Varying Risk Premiums," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 687-709.

    Cited by:

    1. Cakici, Nusret & Fabozzi, Frank J. & Tan, Sinan, 2013. "Size, value, and momentum in emerging market stock returns," Emerging Markets Review, Elsevier, vol. 16(C), pages 46-65.
    2. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    3. Smith, Daniel R., 2007. "Conditional coskewness and asset pricing," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 91-119, January.
    4. Nawalkha, Sanjay K., 1997. "A multibeta representation theorem for linear asset pricing theories," Journal of Financial Economics, Elsevier, vol. 46(3), pages 357-381, December.
    5. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    6. Ahn, Seung C. & Gadarowski, Christopher, 2004. "Small sample properties of the GMM specification test based on the Hansen-Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 109-132, January.
    7. Ravi Jagannathan & Zhenyu Wang, 1996. "The conditional CAPM and the cross-section of expected returns," Staff Report 208, Federal Reserve Bank of Minneapolis.
    8. Campbell R. Harvey & Bruno Solnik & Guofu Zhou, 2002. "What Determines Expected International Asset Returns?," Annals of Economics and Finance, Society for AEF, vol. 3(2), pages 249-298, November.
    9. Seung C. Ahn & Young H. Lee & Peter Schmidt, 2007. "Panel Data Models with Multiple Time-Varying Individual Effects," Working Papers 0702, University of Crete, Department of Economics.
    10. Scott Gilbert & Petr Zemčík, 2005. "Testing for Latent Factors in Models with Autocorrelation and Heteroskedasticity of Unknown Form," Southern Economic Journal, John Wiley & Sons, vol. 72(1), pages 236-252, July.
    11. Huang, Roger D. & Lin, Charles S. Y., 1996. "An analysis of nonlinearities in term premiums and forward rates," Journal of Empirical Finance, Elsevier, vol. 3(4), pages 347-368, December.
    12. Raymond Kan & Guofu Zhou, 1999. "A Critique of the Stochastic Discount Factor Methodology," CEMA Working Papers 12, China Economics and Management Academy, Central University of Finance and Economics.
    13. Zhou, Guofu, 1999. "Security factors as linear combinations of economic variables," Journal of Financial Markets, Elsevier, vol. 2(4), pages 403-432, November.
    14. Zhou, Guofu, 1995. "Small sample rank tests with applications to asset pricing," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 71-93, March.
    15. Jay Shanken & Guofu Zhou, 2007. "Estimating and testing beta pricing models: Alternative methods and their performance in simulations," CEMA Working Papers 275, China Economics and Management Academy, Central University of Finance and Economics.
    16. Guofu Zhou & Yingzi Zhu, 2015. "Macroeconomic Volatilities and Long-Run Risks of Asset Prices," Management Science, INFORMS, vol. 61(2), pages 413-430, February.
    17. Mika Vaihekoski, 1998. "Short-term returns and the predictability of Finnish stock returns," Finnish Economic Papers, Finnish Economic Association, vol. 11(1), pages 19-36, Spring.
    18. Klein, Rudolf F. & Chow, Victor K., 2013. "Orthogonalized factors and systematic risk decomposition," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(2), pages 175-187.
    19. Hung-Gay Fung & Wai Lee & Wai Kin Leung, 2000. "Segmentation Of The A- And B-Share Chinese Equity Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 23(2), pages 179-195, June.
    20. Velu, Raja & Zhou, Guofu, 1999. "Testing multi-beta asset pricing models," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 219-241, September.
    21. Yiying Cheng & Yaozhong Hu & Hongwei Long, 2020. "Generalized moment estimators for $$\alpha $$α-stable Ornstein–Uhlenbeck motions from discrete observations," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 53-81, April.
    22. Quintos, Carmela E., 1998. "Analysis of cointegration vectors using the GMM approach," Journal of Econometrics, Elsevier, vol. 85(1), pages 155-188, July.
    23. Kallberg, Jarl & Pasquariello, Paolo, 2008. "Time-series and cross-sectional excess comovement in stock indexes," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 481-502, June.
    24. Pin-Huang Chou & Guofu Zhou, 2006. "Using Bootstrap to Test Portfolio Efficiency," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 217-249, November.

  37. Harvey, Campbell R. & Zhou, Guofu, 1993. "International asset pricing with alternative distributional specifications," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 107-131, June.
    See citations under working paper version above.
  38. Zhou, Guofu, 1993. "Asset-Pricing Tests under Alternative Distributions," Journal of Finance, American Finance Association, vol. 48(5), pages 1927-1942, December.

    Cited by:

    1. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    2. Dufour, Jean-Marie & Beaulieu, Marie-Claude & Khalaf, Lynda, 2003. "Testing mean-variance efficiency in CAPM with possibly non-gaussian errors: an exact simulation-based approach," Discussion Paper Series 1: Economic Studies 2003,01, Deutsche Bundesbank.
    3. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    4. Prono, Todd, 2015. "Market proxies as factors in linear asset pricing models: Still living with the roll critique," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 36-53.
    5. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.
    6. Mauleon, Ignacio, 2003. "Financial densities in emerging markets: an application of the multivariate ES density," Emerging Markets Review, Elsevier, vol. 4(2), pages 197-223, June.
    7. Wei Liu & James W. Kolari, 2022. "Multifactor Market Indexes," JRFM, MDPI, vol. 15(4), pages 1-26, March.
    8. Ray, Surajit & Savin, N.E. & Tiwari, Ashish, 2009. "Testing the CAPM revisited," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 721-733, December.
    9. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    10. Gilberto Paula & Francisco Jose Cysneiros, 2009. "Systematic risk estimation in symmetric models," Applied Economics Letters, Taylor & Francis Journals, vol. 16(2), pages 217-221.
    11. Danilo Leal & Rodrigo Jiménez & Marco Riquelme & Víctor Leiva, 2023. "Elliptical Capital Asset Pricing Models: Formulation, Diagnostics, Case Study with Chilean Data, and Economic Rationale," Mathematics, MDPI, vol. 11(6), pages 1-27, March.
    12. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
    13. Pin-Huang Chou, 2000. "Alternative Tests Of The Zero-Beta Capm," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 23(4), pages 469-493, December.
    14. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    15. Feng, Long & Lan, Wei & Liu, Binghui & Ma, Yanyuan, 2022. "High-dimensional test for alpha in linear factor pricing models with sparse alternatives," Journal of Econometrics, Elsevier, vol. 229(1), pages 152-175.
    16. Landsman, Zinoviy, 2004. "On the generalization of Esscher and variance premiums modified for the elliptical family of distributions," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 563-579, December.
    17. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
    18. Oussama Chakroun & Georges Dionne & Amélie Dugas-Sampara, 2006. "Empirical Evaluation of Investor Rationality in the Asset Allocation Puzzle," Cahiers de recherche 0635, CIRPEE.
    19. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2016. "On the properties of the constrained Hansen–Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 121-150.
    20. Li, Yong & Zeng, Tao & Yu, Jun, 2014. "A new approach to Bayesian hypothesis testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 602-612.
    21. Haim Levy, 2010. "The CAPM is Alive and Well: A Review and Synthesis," European Financial Management, European Financial Management Association, vol. 16(1), pages 43-71, January.
    22. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.
    23. Francesco Giurda & Elias Tzavalis, 2004. "Is the Currency Risk Priced in Equity Markets?," Working Papers 511, Queen Mary University of London, School of Economics and Finance.
    24. Sermin Gungor & Richard Luger, 2013. "Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances," Staff Working Papers 13-16, Bank of Canada.
    25. Ayub, Usman & Shah, Syed Zulfiqar Ali & Abbas, Qaisar, 2015. "Robust analysis for downside risk in portfolio management for a volatile stock market," Economic Modelling, Elsevier, vol. 44(C), pages 86-96.
    26. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2010. "Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 763-782, September.
    27. Jarl G. Kallberg & Crocker H. Liu & Paolo Pasquariello, 2014. "On the Price Comovement of U.S. Residential Real Estate Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(1), pages 71-108, March.
    28. N. Groenewold & P. Fraser, 1998. "Tests of Asset-pricing Models: How important is the IID-normal assumptions?," Economics Discussion / Working Papers 98-20, The University of Western Australia, Department of Economics.
    29. Taras Bodnar & Arjun K. Gupta & Valdemar Vitlinskyi & Taras Zabolotskyy, 2019. "Statistical Inference for the Beta Coefficient," Risks, MDPI, vol. 7(2), pages 1-14, May.
    30. Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
    31. Kaplanski, Guy, 2004. "Traditional beta, downside risk beta and market risk premiums," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(5), pages 636-653, December.
    32. Pankaj Agrrawal, 2023. "The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties," Mathematics, MDPI, vol. 11(9), pages 1-19, May.
    33. Jean-Marie Dufour & Lynda Khalaf & Marcel Voia, 2013. "Finite-sample resampling-based combined hypothesis tests, with applications to serial correlation and predictability," CIRANO Working Papers 2013s-40, CIRANO.
    34. Taras Bodnar & Stepan Mazur & Krzysztof Podgórski, 2017. "A test for the global minimum variance portfolio for small sample and singular covariance," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(3), pages 253-265, July.
    35. Roy, Vivekananda & Hobert, James P., 2010. "On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1190-1202, May.
    36. Ando, Masakazu & Hodoshima, Jiro, 2006. "The robustness of asset pricing models: Coskewness and cokurtosis," Finance Research Letters, Elsevier, vol. 3(2), pages 133-146, June.
    37. Kais Dachraoui & Georges Dionne, 2007. "Conditions Ensuring the Decomposition of Asset Demand for All Risk-Averse Investors," The European Journal of Finance, Taylor & Francis Journals, vol. 13(5), pages 397-404.
    38. Fischer, Matthias J., 2007. "Are correlations constant over time? Application of the CC-TRIGt-test to return series from different asset classes," SFB 649 Discussion Papers 2007-012, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    39. Muhammad, Irfan, 2012. "Non-standardized form of CAPM and stock returns," MPRA Paper 35604, University Library of Munich, Germany.
    40. Kallberg, Jarl & Pasquariello, Paolo, 2008. "Time-series and cross-sectional excess comovement in stock indexes," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 481-502, June.
    41. Majumder, Debasish, 2014. "Asset pricing for inefficient markets: Evidence from China and India," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 282-291.
    42. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2012. "Analytical solution for the constrained Hansen-Jagannathan distance under multivariate ellipticity," FRB Atlanta Working Paper 2012-18, Federal Reserve Bank of Atlanta.
    43. Pin-Huang Chou & Guofu Zhou, 2006. "Using Bootstrap to Test Portfolio Efficiency," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 217-249, November.
    44. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2010. "On the Hansen-Jagannathan distance with a no-arbitrage constraint," FRB Atlanta Working Paper 2010-04, Federal Reserve Bank of Atlanta.

  39. Zhou, Guofu, 1991. "Small sample tests of portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 30(1), pages 165-191, November.

    Cited by:

    1. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-Fit in Multivariate Regressions with Application to Asset Pricing Models," Cahiers de recherche 07-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Dufour, Jean-Marie & Beaulieu, Marie-Claude & Khalaf, Lynda, 2003. "Testing mean-variance efficiency in CAPM with possibly non-gaussian errors: an exact simulation-based approach," Discussion Paper Series 1: Economic Studies 2003,01, Deutsche Bundesbank.
    3. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models," Cahiers de recherche 2003-08, Universite de Montreal, Departement de sciences economiques.
    4. Marie Briere & Bastien Drut & Valérie Mignon & Kim Oosterlinck & Ariane Szafarz, 2012. "Is the Market Portfolio Efficient? A New Test of Mean-Variance Efficiency when All Assets Are Risky," Working Papers CEB 12-003, ULB -- Universite Libre de Bruxelles.
    5. Gopal K. Basak & Ravi Jagannathan & Tongshu Ma, 2009. "Jackknife Estimator for Tracking Error Variance of Optimal Portfolios," Management Science, INFORMS, vol. 55(6), pages 990-1002, June.
    6. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    7. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
    8. Pin-Huang Chou, 2000. "Alternative Tests Of The Zero-Beta Capm," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 23(4), pages 469-493, December.
    9. Marie Brière & Bastien Drut & Valérie Mignon & Kim Oosterlinck & Ariane Szafarz, 2011. "Is the Market Portfolio Efficient? A New Test to Revisit the Roll (1977) versus Levy and Roll (2010) Controversy," Working Papers hal-04140988, HAL.
    10. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    11. Raymond Kan & Guofu Zhou, 1999. "A Critique of the Stochastic Discount Factor Methodology," CEMA Working Papers 12, China Economics and Management Academy, Central University of Finance and Economics.
    12. Levy, Moshe & Levy, Haim, 2015. "Keeping up with the Joneses and optimal diversification," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 29-38.
    13. Diacogiannis, George & Ioannidis, Christos, 2022. "Linear beta pricing with efficient/inefficient benchmarks and short-selling restrictions," International Review of Financial Analysis, Elsevier, vol. 81(C).
    14. Zhou, Guofu, 1995. "Small sample rank tests with applications to asset pricing," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 71-93, March.
    15. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2009. "Finite sample multivariate tests of asset pricing models with coskewness," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2008-2021, April.
    16. Enrique Sentana, 2008. "The Econometrics of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
    17. G. P. Diacogiannis, 1999. "A three-dimensional risk-return relationship based upon the inefficiency of a portfolio: derivation and implications," The European Journal of Finance, Taylor & Francis Journals, vol. 5(3), pages 225-235.
    18. Velu, Raja & Zhou, Guofu, 1999. "Testing multi-beta asset pricing models," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 219-241, September.
    19. Ai He & Guofu Zhou, 2023. "Diagnostics for asset pricing models," Financial Management, Financial Management Association International, vol. 52(4), pages 617-642, December.
    20. Philip Gray & Egon Kalotay & Julie McIvor, 1998. "Testing the Multivariate Normality of Australian Stock Returns," Australian Journal of Management, Australian School of Business, vol. 23(2), pages 135-150, December.
    21. Balatti, Mirco & Brooks, Chris & Kappou, Konstantina, 2017. "Fundamental indexation revisited: New evidence on alpha," International Review of Financial Analysis, Elsevier, vol. 51(C), pages 1-15.
    22. Walsh, David M. & Walsh, Kathleen D. & Evans, John P., 1998. "Assessing estimation error in a tracking error variance minimisation framework," Pacific-Basin Finance Journal, Elsevier, vol. 6(1-2), pages 175-192, May.
    23. Todd Prono, 2006. "GARCH-based identification of triangular systems with an application to the CAPM: still living with the roll critique," Working Papers 07-1, Federal Reserve Bank of Boston.

  40. Harvey, Campbell R. & Zhou, Guofu, 1990. "Bayesian inference in asset pricing tests," Journal of Financial Economics, Elsevier, vol. 26(2), pages 221-254, August.

    Cited by:

    1. Sourish Das & Rituparna Sen, 2021. "Sparse Portfolio Selection via Bayesian Multiple Testing," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 585-617, November.
    2. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2023. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 126151, London School of Economics and Political Science, LSE Library.
    3. Wang, Zhenyu, 1998. "Efficiency loss and constraints on portfolio holdings," Journal of Financial Economics, Elsevier, vol. 48(3), pages 359-375, June.
    4. Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
    5. Zhenyu Wang & Xiaoyan Zhang, 2006. "Empirical evaluation of asset pricing models: arbitrage and pricing errors over contingent claims," Staff Reports 265, Federal Reserve Bank of New York.
    6. Pin-Huang Chou, 1996. "Using Bootstrap to Test Mean-Variance Efficiency of a Given Portfolio," Finance 9609002, University Library of Munich, Germany.
    7. Michael Rockinger & Eric Jondeau, 2002. "Asset Allocation in Transition Economies," Working Papers hal-00597773, HAL.
    8. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-587.
    9. Chou, Pin-Huang, 1997. "A Gibbs sampling approach to the estimation of linear regression models under daily price limits," Pacific-Basin Finance Journal, Elsevier, vol. 5(1), pages 39-62, February.
    10. Chinco, Alex & Neuhierl, Andreas & Weber, Michael, 2021. "Estimating the anomaly base rate," Journal of Financial Economics, Elsevier, vol. 140(1), pages 101-126.
    11. Tu, Jun & Zhou, Guofu, 2004. "Data-generating process uncertainty: What difference does it make in portfolio decisions?," Journal of Financial Economics, Elsevier, vol. 72(2), pages 385-421, May.
    12. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    13. Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
    14. Campbell R. Harvey & Guofu Zhou, 1993. "International asset pricing with alternative distributional specifications," CEMA Working Papers 277, China Economics and Management Academy, Central University of Finance and Economics.
    15. Fletcher, Jonathan, 2018. "Bayesian tests of global factor models," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 279-289.
    16. Cederburg, Scott & O’Doherty, Michael S., 2015. "Asset-pricing anomalies at the firm level," Journal of Econometrics, Elsevier, vol. 186(1), pages 113-128.
    17. Erik Kole & Reza Brink, "undated". "Constructing and Using Double-adjusted Alphas to Analyze Mutual Fund Performance," Tinbergen Institute Discussion Papers 19-029/IV, Tinbergen Institute.
    18. Michael Rockinger & Eric Jondeau, 2001. "Portfolio allocation in transition economies," Working Papers hal-00601482, HAL.
    19. Kandel, S. & McCulloch, R. & Stambaugh, R.F., 1991. "Bayesian Inference and Portfolio Efficiency," Weiss Center Working Papers 8-91, Wharton School - Weiss Center for International Financial Research.
    20. Ouysse, Rachida & Kohn, Robert, 2010. "Bayesian variable selection and model averaging in the arbitrage pricing theory model," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3249-3268, December.
    21. Harvey, Campbell R., 2001. "The specification of conditional expectations," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 573-637, December.
    22. Pin-Huang Chou, 2000. "Alternative Tests Of The Zero-Beta Capm," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 23(4), pages 469-493, December.
    23. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    24. Marie Briere & Ariane Szafarz, 2021. "When it Rains, it Pours: Multifactor Asset Management in Good and Bad Times," Working Papers CEB 21-002, ULB -- Universite Libre de Bruxelles.
    25. Fletcher, Jonathan, 2019. "Model comparison tests of linear factor models in U.K. stock returns," Finance Research Letters, Elsevier, vol. 28(C), pages 281-291.
    26. Doron Avramov & Si Cheng & Lior Metzker & Stefan Voigt, 2023. "Integrating Factor Models," Journal of Finance, American Finance Association, vol. 78(3), pages 1593-1646, June.
    27. Manuel Ammann & Michael Verhofen, 2008. "Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach," European Financial Management, European Financial Management Association, vol. 14(3), pages 391-418, June.
    28. Stambaugh, Robert F., 1997. "Analyzing investments whose histories differ in length," Journal of Financial Economics, Elsevier, vol. 45(3), pages 285-331, September.
    29. Enrique Sentana, 2008. "The Econometrics of Mean-Variance Efficiency Tests: A Survey," Working Papers wp2008_0807, CEMFI.
    30. Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
    31. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    32. Kan, Raymond & Wang, Xiaolu & Zheng, Xinghua, 2024. "In-sample and out-of-sample Sharpe ratios of multi-factor asset pricing models," Journal of Financial Economics, Elsevier, vol. 155(C).
    33. Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 959-986, August.
    34. Cosemans, M. & Frehen, R.G.P. & Schotman, P.C. & Bauer, R.M.M.J., 2009. "Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice," MPRA Paper 23557, University Library of Munich, Germany.
    35. Francisco Barillas & Jay Shanken, 2018. "Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 73(2), pages 715-754, April.
    36. Pin-Huang Chou & Guofu Zhou, 2006. "Using Bootstrap to Test Portfolio Efficiency," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 217-249, November.
    37. Johnstone, David, 2022. "Accounting research and the significance test crisis," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 89(C).
    38. Walsh, David M. & Walsh, Kathleen D. & Evans, John P., 1998. "Assessing estimation error in a tracking error variance minimisation framework," Pacific-Basin Finance Journal, Elsevier, vol. 6(1-2), pages 175-192, May.
    39. Malefaki, Valia, 2015. "On Flexible Linear Factor Stochastic Volatility Models," MPRA Paper 62216, University Library of Munich, Germany.
    40. Ferson, Wayne E & Korajczyk, Robert A, 1995. "Do Arbitrage Pricing Models Explain the Predictability of Stock Returns?," The Journal of Business, University of Chicago Press, vol. 68(3), pages 309-349, July.

Chapters

  1. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    3. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    4. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    5. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    6. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    7. Yingying Xu & Jichang Zhao, 2022. "Can sentiments on macroeconomic news explain stock returns? Evidence form social network data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2073-2088, April.
    8. Philippe Bacchetta & Simon Tièche & Eric van Wincoop, 2020. "International Portfolio Choice with Frictions: Evidence from Mutual Funds," Swiss Finance Institute Research Paper Series 20-46, Swiss Finance Institute.
    9. Stelios Bekiros & Rangan Gupta & Anandamayee Majumdar, 2015. "Incorporating Economic Policy Uncertainty in US Equity Premium Models: A Nonlinear Predictability Analysis," Working Papers 201545, University of Pretoria, Department of Economics.
    10. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    11. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    12. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    13. Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2016. "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(3), pages 273-291.
    14. Paresh K. Narayan & Rangan Gupta, 2014. "Has Oil Pirce Predicted Stock Returns for Over a Century?," Working Papers 201446, University of Pretoria, Department of Economics.
    15. Wang, Yubao & Huang, Xiaozhou & Huang, Zhendong, 2024. "Energy-related uncertainty and Chinese stock market returns," Finance Research Letters, Elsevier, vol. 62(PB).
    16. Theologos Dergiades & Panos K. Pouliasis, 2021. "Should Stock Returns Predictability be hooked on Long Horizon Regressions?," Discussion Paper Series 2021_03, Department of Economics, University of Macedonia, revised Feb 2021.
    17. Richard K. Crump & Miro Everaert & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Staff Reports 850, Federal Reserve Bank of New York.
    18. Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.
    19. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    20. Nikolaos Antonakakis & Rangan Gupta & Aviral K. Tiwari, 2016. "Time-Varying Correlations between Inflation and Stock Prices in the United States over the Last Two Centuries," Working Papers 201605, University of Pretoria, Department of Economics.
    21. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    22. Jamal Bouoiyour & Refk Selmi, 2017. "Are Trump and Bitcoin Good Partners?," Working Papers hal-01480031, HAL.
    23. Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018. "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, vol. 70(C), pages 334-356.
    24. Møller, Stig V. & Rangvid, Jesper, 2015. "End-of-the-year economic growth and time-varying expected returns," Journal of Financial Economics, Elsevier, vol. 115(1), pages 136-154.
    25. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "The role of time‐varying rare disaster risks in predicting bond returns and volatility," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 327-340, July.
    26. Kostakis, Alexandros & Magdalinos, Tassos & Stamatogiannis, Michalis P., 2023. "Taking stock of long-horizon predictability tests: Are factor returns predictable?," Journal of Econometrics, Elsevier, vol. 237(2).
    27. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    28. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    29. Rangan Gupta & Hardik A. Marfatia & Christian Pierdzioch & Afees A. Salisu, 2020. "Machine Learning Predictions of Housing Market Synchronization across US States: The Role of Uncertainty," Working Papers 202077, University of Pretoria, Department of Economics.
    30. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    31. Shi, Qi & Li, Bin, 2022. "Further evidence on financial information and economic activity forecasts in the United States," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    32. Massimo Guidolin & Alexei Orlov, 2018. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," BAFFI CAREFIN Working Papers 1890, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    33. Gupta, Rangan & Kanda, Patrick & Tiwari, Aviral Kumar & Wohar, Mark E., 2019. "Time-varying predictability of oil market movements over a century of data: The role of US financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    34. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    35. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    36. Mingwei Sun & Paskalis Glabadanidis, 2022. "Can technical indicators predict the Chinese equity risk premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 114-142, March.
    37. Rangan Gupta & Shawkat Hammoudeh & Mampho P. Modise & Duc Khuong Nguyen, 2013. "Can Economic Uncertainty, Financial Stress and Consumer Sentiments Predict U.S. Equity Premium?," Working Papers 201351, University of Pretoria, Department of Economics.
    38. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    39. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Role of hedging on crypto returns predictability: A new habit-based explanation," Finance Research Letters, Elsevier, vol. 55(PB).
    40. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2012. "Prediction Markets for Economic Forecasting," CESifo Working Paper Series 3884, CESifo.
    41. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    42. Apergis, Nicholas & Gupta, Rangan, 2017. "Can (unusual) weather conditions in New York predict South African stock returns?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 377-386.
    43. Peter Christoffersen & Mathieu Fournier & Kris Jacobs & Mehdi Karoui, 2015. "Option-Based Estimation of the Price of Co-Skewness and Co-Kurtosis Risk," CREATES Research Papers 2015-54, Department of Economics and Business Economics, Aarhus University.
    44. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    45. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    46. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    47. Cenedese, Gino & Mallucci, Enrico, 2016. "What moves international stock and bond markets?," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 94-113.
    48. Christina Christou & Rangan Gupta, 2016. "Forecasting Equity Premium in a Panel of OECD Countries: The Role of Economic Policy Uncertainty," Working Papers 201622, University of Pretoria, Department of Economics.
    49. Spierdijk, Laura & Umar, Zaghum, 2015. "Stocks, bonds, T-bills and inflation hedging: From great moderation to great recession," Journal of Economics and Business, Elsevier, vol. 79(C), pages 1-37.
    50. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    51. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
    52. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    53. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    54. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2015. "International Stock Return Predictability: Is the Role of U.S. Time-Varying?," Working Papers 201524, University of Pretoria, Department of Economics.
    55. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
    56. Afees A. Salisu & Rangan Gupta & Idris A. Adediran, 2021. "The Effect of US Uncertainty Shock on International Equity Markets: The Role of the Global Financial Cycle," Working Papers 202136, University of Pretoria, Department of Economics.
    57. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    58. Imen Dakhlaoui & Chaker Aloui, 2016. "The Interactive Relationship Between the US Economic Policy Uncertainty and BRIC Stock Markets," International Economics, CEPII research center, issue 146, pages 141-157.
    59. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    60. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    61. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    62. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    63. Cao, Zhen & Han, Liyan & Wei, Xinbei & Zhang, Qunzi, 2022. "Fear in commodity return prediction," Finance Research Letters, Elsevier, vol. 46(PB).
    64. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
    65. Haibin Xie & Shouyang Wang, 2015. "Risk-return trade-off, information diffusion, and U.S. stock market predictability," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-20, December.
    66. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    67. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    68. Chang, Tsangyao & Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian, 2019. "Predicting stock market movements with a time-varying consumption-aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 458-467.
    69. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    70. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2023. "Tail risks and forecastability of stock returns of advanced economies: evidence from centuries of data," The European Journal of Finance, Taylor & Francis Journals, vol. 29(4), pages 466-481, March.
    71. Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, vol. 28(1), pages 47-59, February.
    72. Bekiros, Stelios & Gupta, Rangan & Kyei, Clement, 2016. "On economic uncertainty, stock market predictability and nonlinear spillover effects," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 184-191.
    73. Balcilar, Mehmet & Bathia, Deven & Demirer, Riza & Gupta, Rangan, 2021. "Credit ratings and predictability of stock return dynamics of the BRICS and the PIIGS: Evidence from a nonparametric causality-in-quantiles approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 290-302.
    74. Cenedese, Gino & Payne, Richard & Sarno, Lucio & Valente, Giorgio, 2015. "What do stock markets tell us about exchange rates?," Bank of England working papers 537, Bank of England.
    75. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    76. Umar, Zaghum, 2017. "Islamic vs conventional equities in a strategic asset allocation framework," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 1-10.
    77. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    78. Cunha, Ronan & Pereira, Pedro L. Valls, 2015. "Automatic model selection for forecasting Brazilian stock returns," Textos para discussão 398, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    79. Gupta, Rangan & Pierdzioch, Christian & Selmi, Refk & Wohar, Mark E., 2018. "Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model☆," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 87-96.
    80. Zhang, Yue-Jun & Li, Zhao-Chen, 2021. "Forecasting the stock returns of Chinese oil companies: Can investor attention help?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 531-555.
    81. Philippe Goulet Coulombe, 2020. "To Bag is to Prune," Papers 2008.07063, arXiv.org, revised Sep 2024.
    82. Wu, Shue-Jen & Lee, Wei-Ming, 2015. "Predicting severe simultaneous bear stock markets using macroeconomic variables as leading indicators," Finance Research Letters, Elsevier, vol. 13(C), pages 196-204.
    83. Taofeek O. AYINDE & Farouq A. ADEYEMI, 2023. "Global Evidence of Oil Supply Shocks and Climate Risk a GARCH-MIDAS Approach," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 4(2), pages 1-7.
    84. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch & Mark Wohar, 2016. "Terror Attacks and Stock-Market Fluctuations: Evidence Based on a Nonparametric Causality-in-Quantiles Test for the G7 Countries," Working Papers 201608, University of Pretoria, Department of Economics.
    85. Ayinde, Taofeek O. & Olaniran, Abeeb O. & Abolade, Onomeabure C. & Ogbonna, Ahamuefula Ephraim, 2023. "Technology shocks - Gold market connection: Is the effect episodic to business cycle behaviour?," Resources Policy, Elsevier, vol. 84(C).
    86. Elie Bouri & Riza Demirer & Rangan Gupta & Hardik A. Marfatia, 2019. "Geopolitical Risks and Movements in Islamic Bond and Equity Markets: A Note," Defence and Peace Economics, Taylor & Francis Journals, vol. 30(3), pages 367-379, April.
    87. Gupta, Rangan & Risse, Marian & Volkman, David A. & Wohar, Mark E., 2019. "The role of term spread and pattern changes in predicting stock returns and volatility of the United Kingdom: Evidence from a nonparametric causality-in-quantiles test using over 250 years of data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 391-405.
    88. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    89. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    90. Haibin Xie & Yuying Sun & Pengying Fan, 2023. "Return direction forecasting: a conditional autoregressive shape model with beta density," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    91. Wenbo Wu & Jiaqi Chen & Liang Xu & Qingyun He & Michael L. Tindall, 2019. "A statistical learning approach for stock selection in the Chinese stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-18, December.
    92. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
    93. Davide Pettenuzzo & Allan Timmermann & Rossen Valkanov, 2013. "Forecasting Stock Returns under Economic Constraints," Working Papers 57, Brandeis University, Department of Economics and International Business School.
    94. Salisu, Afees A. & Bouri, Elie & Gupta, Rangan, 2022. "Out-of-sample predictability of gold market volatility: The role of US Nonfarm Payroll," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 482-488.
    95. Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021. "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, vol. 42(C).
    96. Stelios Bekiros & Rangan Gupta, 2015. "Predicting Stock Returns and Volatility Using Consumption-Aggregate Wealth Ratios: A Nonlinear Approach," Working Papers 201505, University of Pretoria, Department of Economics.
    97. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    98. Christina Christou & Rangan Gupta & Fredj Jawadi, 2017. "Does Inequality Help in Forecasting Equity Premium in a Panel of G7 Countries?," Working Papers 201720, University of Pretoria, Department of Economics.
    99. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "Geopolitical Risks and Stock Market Dynamics of the BRICS," Working Papers 201648, University of Pretoria, Department of Economics.
    100. Christou, Christina & Gupta, Rangan & Hassapis, Christis, 2017. "Does economic policy uncertainty forecast real housing returns in a panel of OECD countries? A Bayesian approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 50-60.
    101. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2021. "Forecasting the Artificial Intelligence Index Returns: A Hybrid Approach," Working Papers 202182, University of Pretoria, Department of Economics.
    102. Rangan Gupta & John W. Muteba Mwamba & Mark E. Wohar, 2016. "The Role of Partisan Conflict in Forecasting the U.S. Equity Premium: A Nonparametric Approach," Working Papers 201686, University of Pretoria, Department of Economics.
    103. Massimo Guidolin & Manuela Pedio, 2018. "Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors," BAFFI CAREFIN Working Papers 1886, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    104. Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
    105. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    106. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    107. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    108. Conlon, Thomas & Cotter, John & Eyiah-Donkor, Emmanuel, 2024. "Forecasting the price of oil: A cautionary note," Journal of Commodity Markets, Elsevier, vol. 33(C).
    109. Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019. "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, vol. 29(C), pages 315-322.
    110. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    111. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    112. Helena Chuliá & Rangan Gupta & Jorge M. Uribe & Mark E. Wohar, 2016. "Impact of US Uncertainties on Emerging and Mature Markets: Evidence from a Quantile-Vector Autoregressive Approach," Working Papers 201656, University of Pretoria, Department of Economics.
    113. Gu, Ailing & Viens, Frederi G. & Yao, Haixiang, 2018. "Optimal robust reinsurance-investment strategies for insurers with mean reversion and mispricing," Insurance: Mathematics and Economics, Elsevier, vol. 80(C), pages 93-109.
    114. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    115. Walid Bahloul & Mehmet Balcilar & Juncal Cunado & Rangan Gupta, 2017. "The Role of Economic and Financial Uncertainties in Predicting Commodity Futures Returns and Volatility: Evidence from a Nonparametric Causality-in-Quantiles Test," Working Papers 201725, University of Pretoria, Department of Economics.
    116. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
    117. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    118. Nonejad, Nima, 2021. "The price of crude oil and (conditional) out-of-sample predictability of world industrial production," Journal of Commodity Markets, Elsevier, vol. 23(C).
    119. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    120. Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023. "Targeting predictors in random forest regression," International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
    121. Liu, Li & Ma, Feng & Wang, Yudong, 2015. "Forecasting excess stock returns with crude oil market data," Energy Economics, Elsevier, vol. 48(C), pages 316-324.
    122. Oğuzhan Çepni & Rangan Gupta & Mark E. Wohar, 2021. "Variants of consumption‐wealth ratios and predictability of U.S. government bond risk premia," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 661-674, June.
    123. Qunzi Zhang, 2021. "One hundred years of rare disaster concerns and commodity prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1891-1915, December.
    124. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    125. Rangan Gupta & Hardik A. Marfatia & Eric Olson, 2020. "Effect of uncertainty on U.S. stock returns and volatility: evidence from over eighty years of high-frequency data," Applied Economics Letters, Taylor & Francis Journals, vol. 27(16), pages 1305-1311, September.
    126. Dai, Zhifeng & Dong, Xiaodi & Kang, Jie & Hong, Lianying, 2020. "Forecasting stock market returns: New technical indicators and two-step economic constraint method," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    127. Ikhlaas Gurrib & Firuz Kamalov & Elgilani E. Alshareif, 2022. "High Frequency Return and Risk Patterns in U.S. Sector ETFs during COVID-19," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 441-456, September.
    128. Brückbauer, Frank, 2022. "Do financial market experts know their theory? New evidence from survey data," ZEW Discussion Papers 20-092, ZEW - Leibniz Centre for European Economic Research, revised 2022.
    129. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    130. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
    131. Philippe Goulet Coulombe, 2021. "To Bag is to Prune," Working Papers 21-03, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Jun 2021.
    132. Abdul RASHID & Aamir JAVED & Zainab JEHAN & Uzma IQBAL, 2022. "Time-Varying Impacts of Macroeconomic Variables on Stock Market Returns and Volatility : Evidence from Pakistan," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 144-166, October.
    133. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    134. Muzhao Jin & Fearghal Kearney & Youwei Li & Yung Chiang Yang, 2020. "Intraday time‐series momentum: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(4), pages 632-650, April.
    135. Patrick Bielstein, 2018. "International asset allocation using the market implied cost of capital," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(1), pages 17-51, February.
    136. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    137. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    138. Nima Nonejad, 2021. "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, vol. 61(2), pages 973-1009, August.
    139. Berardi, Michele, 2021. "Uncertainty, sentiments and time-varying risk premia," MPRA Paper 106922, University Library of Munich, Germany.
    140. Bouri, Elie & Gupta, Rangan & Hosseini, Seyedmehdi & Lau, Chi Keung Marco, 2018. "Does global fear predict fear in BRICS stock markets? Evidence from a Bayesian Graphical Structural VAR model," Emerging Markets Review, Elsevier, vol. 34(C), pages 124-142.
    141. Oguzhan Cepni & Rangan Gupta & Qiang Ji, 2021. "Sentiment Regimes and Reaction of Stock Markets to Conventional and Unconventional Monetary Policies: Evidence from OECD Countries," Working Papers 202126, University of Pretoria, Department of Economics.
    142. Rangan Gupta & Jacobus Nel & Joshua Nielsen & Christian Pierdzioch, 2023. "Stock Market Volatility and Multi-Scale Positive and Negative Bubbles," Working Papers 202310, University of Pretoria, Department of Economics.
    143. Xu Chong Bo & Jianlei Han & Yin Liao & Jing Shi & Wu Yan, 2021. "Do outliers matter? The predictive ability of average skewness on market returns using robust skewness measures," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 3977-4006, September.
    144. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    145. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    146. Amit Goyal & Narasimhan Jegadeesh, 2018. "Cross-Sectional and Time-Series Tests of Return Predictability: What Is the Difference?," The Review of Financial Studies, Society for Financial Studies, vol. 31(5), pages 1784-1824.
    147. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    148. Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023. "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 358-368.
    149. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    150. Bouri, Elie & Gupta, Rangan, 2021. "Predicting Bitcoin returns: Comparing the roles of newspaper- and internet search-based measures of uncertainty," Finance Research Letters, Elsevier, vol. 38(C).
    151. Gupta, Rangan & Sheng, Xin & Pierdzioch, Christian & Ji, Qiang, 2021. "Disaggregated oil shocks and stock-market tail risks: Evidence from a panel of 48 economics," Research in International Business and Finance, Elsevier, vol. 58(C).
    152. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    153. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    154. Nonejad, Nima, 2022. "Equity premium prediction using the price of crude oil: Uncovering the nonlinear predictive impact," Energy Economics, Elsevier, vol. 115(C).
    155. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    156. Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
    157. Rangan Gupta & Xin Sheng & Christian Pierdzioch & Qiang Ji, 2021. "Disaggregated Oil Shocks and Stock-Market Tail Risks: Evidence from a Panel of 48 Countries," Working Papers 202106, University of Pretoria, Department of Economics.
    158. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati & Gupta, Rangan, 2016. "A historical analysis of the US stock price index using empirical mode decomposition over 1791-2015," Economics Discussion Papers 2016-9, Kiel Institute for the World Economy (IfW Kiel).
    159. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    160. Jiang, Yuexiang & Fu, Tao & Long, Huaigang & Zaremba, Adam & Zhou, Wenyu, 2022. "Real estate climate index and aggregate stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    161. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
    162. Eric Jondeau & Xuewu Wang & Zhipeng Yan & Qunzi Zhang, 2020. "Skewness and index futures return," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1648-1664, November.
    163. Stig V. Møller & Jesper Rangvid, 2018. "Global Economic Growth and Expected Returns Around the World: The End-of-the-Year Effect," Management Science, INFORMS, vol. 64(2), pages 573-591, February.
    164. Vasilios Plakandaras & Rangan Gupta & Wing-Keung Wong, 2018. "Point and Density Forecasts of Oil Returns: The Role of Geopolitical Risks," Working Papers 201847, University of Pretoria, Department of Economics.
    165. David E. Rapach & Matthew C. Ringgenberg & Guofu Zhou, 2016. "Short interest and aggregate stock returns," CEMA Working Papers 716, China Economics and Management Academy, Central University of Finance and Economics.
    166. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    167. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    168. Liu, Li & Zhang, Tao, 2015. "Economic policy uncertainty and stock market volatility," Finance Research Letters, Elsevier, vol. 15(C), pages 99-105.
    169. Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
    170. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    171. Mobeen Ur Rehman & Wafa Ghardallou & Nasir Ahmad & Xuan Vinh Vo & Sang Hoon Kang, 2024. "Does effect of risk and uncertainties on US sectoral returns differ across different investment horizons and market conditions," Risk Management, Palgrave Macmillan, vol. 26(1), pages 1-49, February.
    172. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    173. Zuzanna Karolak, 2021. "Energy prices forecasting using nonlinear univariate models," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 577-598.
    174. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    175. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2018. "Forecasting (Good and Bad) Realized Exchange-Rate Volatility: Is there a Role for Realized Skewness and Kurtosis?," Working Papers 201879, University of Pretoria, Department of Economics.
    176. Hounyo, Ulrich & Lahiri, Kajal, 2023. "Estimating the variance of a combined forecast: Bootstrap-based approach," Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
    177. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    178. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
    179. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    180. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
    181. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    182. Afees A. Salisu & Rangan Gupta, 2021. "Commodity Prices and Forecastability of South African Stock Returns Over a Century: Sentiments versus Fundamentals," Working Papers 202144, University of Pretoria, Department of Economics.
    183. Christina Christou & Juncal Cunado & Rangan Gupta & Christis Hassapis, 2016. "Economic Policy Uncertainty and Stock Market Returns in Pacific-Rim Countries: Evidence based on a Bayesian Panel VAR Model," Working Papers 201661, University of Pretoria, Department of Economics.
    184. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    185. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
    186. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2017. "Do cay and cayMS predict stock and housing returns? Evidence from a nonparametric causality test," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 269-279.
    187. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    188. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    189. Dbouk, Wassim & Moussawi-Haidar, Lama & Jaber, Mohamad Y., 2020. "The effect of economic uncertainty on inventory and working capital for manufacturing firms," International Journal of Production Economics, Elsevier, vol. 230(C).
    190. Hammami, Yacine & Zhu, Jie, 2020. "Understanding time-varying short-horizon predictability✰," Finance Research Letters, Elsevier, vol. 32(C).
    191. Buncic, Daniel & Tischhauser, Martin, 2017. "Macroeconomic factors and equity premium predictability," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 621-644.
    192. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    193. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    194. Nonejad, Nima, 2018. "Déjà vol oil? Predicting S&P 500 equity premium using crude oil price volatility: Evidence from old and recent time-series data," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 260-270.
    195. Giulia Dal Pra & Massimo Guidolin & Manuela Pedio & Fabiola Vasile, 2016. "Do Regimes in Excess Stock Return Predictability Create Economic Value? An Out-of-Sample Portfolio Analysis," BAFFI CAREFIN Working Papers 1637, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    196. Nygaard, Knut & Sørensen, Lars Qvigstad, 2024. "Betting on war? Oil prices, stock returns, and extreme geopolitical events," Energy Economics, Elsevier, vol. 136(C).
    197. Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "Variants of Consumption-Wealth Ratios and Predictability of U.S. Government Bond Risk Premia: Old is still Gold," Working Papers 201912, University of Pretoria, Department of Economics.
    198. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    199. Dierkes, Maik & Germer, Stephan & Sejdiu, Vulnet, 2020. "Probability distortion, asset prices, and economic growth," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 84(C).
    200. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    201. Li, Jun & Wang, Huijun & Yu, Jianfeng, 2021. "Aggregate expected investment growth and stock market returns," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 618-638.
    202. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    203. Dahlquist, Magnus & Hasseltoft, Henrik, 2020. "Economic momentum and currency returns," Journal of Financial Economics, Elsevier, vol. 136(1), pages 152-167.
    204. Eriksen, Jonas N., 2017. "Expected Business Conditions and Bond Risk Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1667-1703, August.
    205. Tahir Suleman & Rangan Gupta & Mehmet Balcilar, 2016. "Does Country Risks Predict Stock Returns and Volatility? Evidence from a Nonparametric Approach," Working Papers 201675, University of Pretoria, Department of Economics.
    206. Rangan Gupta & Shawkat Hammoudeh & Beatrice D. Simo-Kengne & Soodabeh Sarafrazi, 2013. "Can the Sharia-Based Islamic Stock Market Returns be Forecasted Using Large Number of Predictors and Models?," Working Papers 201381, University of Pretoria, Department of Economics.
    207. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    208. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    209. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    210. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    211. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    212. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    213. Møller, Stig V. & Nørholm, Henrik & Rangvid, Jesper, 2014. "Consumer confidence or the business cycle: What matters more for European expected returns?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 230-248.
    214. Adrian Fernandez-Perez & Ana-Maria Fuertes & Joelle Miffre, 2017. "Commodity Markets, Long-Run Predictability, and Intertemporal Pricing," Review of Finance, European Finance Association, vol. 21(3), pages 1159-1188.
    215. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
    216. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    217. Edson VENGESAI & Adefemi A. OBALADE & Paul-Francois MUZINDUTSI, 2021. "Country Risk Dynamics and Stock Market Volatility: Evidence from the JSE Cross-Sector Analysis," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 5(2), pages 63-84.
    218. Ilias Tsiakas & Jiahan Li & Haibin Zhang, 2020. "Equity Premium Prediction and the State of the Economy," Working Paper series 20-16, Rimini Centre for Economic Analysis.
    219. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part II: Analysis of the Models," Papers 1401.1891, arXiv.org, revised Feb 2016.
    220. Lof, Matthijs & Nyberg, Henri, 2024. "Discount rates and cash flows: A local projection approach," Journal of Banking & Finance, Elsevier, vol. 162(C).
    221. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
    222. Chen Zhang, 2022. "Asset Pricing and Deep Learning," Papers 2209.12014, arXiv.org.
    223. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Lasisi, Lukman & Olaniran, Abeeb, 2022. "Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    224. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    225. Baur, Dirk G. & Dichtl, Hubert & Drobetz, Wolfgang & Wendt, Viktoria-Sophie, 2020. "Investing in gold – Market timing or buy-and-hold?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    226. Rangan Gupta & Christian Pierdzioch & Afees A. Salisu, 2020. "Oil-Price Uncertainty and the U.K. Unemployment Rate: A Forecasting Experiment with Random Forests Using 150 Years of Data," Working Papers 202095, University of Pretoria, Department of Economics.
    227. Afees A. Salisu & Abeeb Olaniran, 2022. "The U.S. Nonfarm Payroll and the out-of-sample predictability of output growth for over six decades," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4663-4673, December.
    228. Antonakakis, Nikolaos & Gupta, Rangan & Tiwari, Aviral K., 2017. "Has the correlation of inflation and stock prices changed in the United States over the last two centuries?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1-8.
    229. Kenwin Maung, 2021. "Estimating high-dimensional Markov-switching VARs," Papers 2107.12552, arXiv.org.
    230. Carr, Peter & Wu, Liuren, 2016. "Analyzing volatility risk and risk premium in option contracts: A new theory," Journal of Financial Economics, Elsevier, vol. 120(1), pages 1-20.
    231. Ciner, Cetin, 2022. "Predicting the equity market risk premium: A model selection approach," Economics Letters, Elsevier, vol. 215(C).
    232. Li, Yi & Shen, Dehua & Wang, Pengfei & Zhang, Wei, 2020. "Does intraday time-series momentum exist in Chinese stock index futures market?," Finance Research Letters, Elsevier, vol. 35(C).
    233. Xidonas, Panos & Doukas, Haris & Hassapis, Christis, 2021. "Grouped data, investment committees & multicriteria portfolio selection," Journal of Business Research, Elsevier, vol. 129(C), pages 205-222.
    234. Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.
    235. Lee, Chien-Chiang & Chen, Mei-Ping, 2020. "Do natural disasters and geopolitical risks matter for cross-border country exchange-traded fund returns?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    236. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2023. "A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    237. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    238. Spierdijk, Laura & Umar, Zaghum, 2014. "Stocks for the long run? Evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 217-238.
    239. Jones, Clive, 2015. "Predictability of the daily high and low of the S&P 500 index," MPRA Paper 62664, University Library of Munich, Germany.
    240. Shi, Qi, 2023. "The RP-PCA factors and stock return predictability: An aligned approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    241. Møller, Stig V. & Sander, Magnus, 2017. "Dividends, earnings, and predictability," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 153-163.
    242. Nicholas Apergis & Matteo Bonato & Rangan Gupta & Clement Kyei, 2016. "Does Geopolitical Risks Predict Stock Returns and Volatility of Leading Defense Companies? Evidence from a Nonparametric Approach," Working Papers 201671, University of Pretoria, Department of Economics.
    243. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    244. Rangan Gupta & Christian Pierdzioch & Refk Selmi & Mark E. Wohar, 2017. "Does Partisan Conflict Predict a Reduction in US Stock Market (Realized) Volatility? Evidence from a Quantile-on-Quantile Regression Model," Working Papers 201744, University of Pretoria, Department of Economics.
    245. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    246. Mehmet Balcilar & Deven Bathia & Riza Demirer & Rangan Gupta, 2017. "Credit Ratings and Predictability of Stock Returns and Volatility of the BRICS and the PIIGS: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201719, University of Pretoria, Department of Economics.
    247. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    248. Zhang, Xincheng, 2024. "Country-level energy-related uncertainties and stock market returns: Insights from the U.S. and China," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    249. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    250. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
    251. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Hedging the extreme risk of cryptocurrency," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    252. Andreas Gruener & Christian Finke, 2018. "Lead-Lag Relationships in International Stock Markets Revisited: Are They Exploitable?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(1), pages 8-30, January.
    253. Dominik Wolff & Ulrich Neugebauer, 2019. "Tree-based machine learning approaches for equity market predictions," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 273-288, July.
    254. Fletcher, Jonathan & Basu, Devraj, 2016. "An examination of the benefits of dynamic trading strategies in U.K. closed-end funds," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 109-118.
    255. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predicting inflation expectations: A habit-based explanation under hedging," International Review of Financial Analysis, Elsevier, vol. 89(C).
    256. Afees A. Salisu & Abdulsalam Abidemi Sikiru, 2021. "Palm Oil Price–Exchange Rate Nexus In Indonesia And Malaysia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 24(2), pages 169-180, June.
    257. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    258. Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Realized Stock-Market Volatility: Do Industry Returns have Predictive Value?," Working Papers 2020107, University of Pretoria, Department of Economics.
    259. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.
    260. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    261. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    262. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    263. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.
    264. Bing Han & Gang Li, 2021. "Information Content of Aggregate Implied Volatility Spread," Management Science, INFORMS, vol. 67(2), pages 1249-1269, February.
    265. Kyoung‐Hun Bae & Peter Dixon, 2018. "Do investors use options and futures to trade on different types of information? Evidence from an aggregate stock index," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 175-198, February.
    266. Bo Yi & Frederi Viens & Baron Law & Zhongfei Li, 2015. "Dynamic portfolio selection with mispricing and model ambiguity," Annals of Finance, Springer, vol. 11(1), pages 37-75, February.
    267. Nicholas Apergis & Rangan Gupta, 2016. "Can Weather Conditions in New York Predict South African Stock Returns?," Working Papers 201634, University of Pretoria, Department of Economics.
    268. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.
    269. Parastoo Mousavi, 2021. "Debt-by-Price Ratio, End-of-Year Economic Growth, and Long-Term Prediction of Stock Returns," Mathematics, MDPI, vol. 9(13), pages 1-18, July.

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