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Pedro Santa-Clara

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. Jose Faias & Miguel Ferreira & Pedro Santa-Clara & Pedro Matos, 2011. "Does Institutional Ownership Matter for International Stock Return Comovement?," EcoMod2011 3038, EcoMod.

    Cited by:

    1. Sebastián García-Andrade, 2019. "Efectos del rebalanceo de los índices de J.P. Morgan en 2014 sobre los rendimientos de los TES en moneda local," Borradores de Economia 1094, Banco de la Republica de Colombia.
    2. Caglayan, Mustafa Onur & Hu, Yu & Xue, Wenjun, 2021. "Mutual fund herding and return comovement in Chinese equities," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    3. Vicente Bermejo & José Campa & Rodolfo Campos & Mohammed Zakriya, 2020. "Do foreign stocks substitute for international diversification?," Post-Print hal-03135756, HAL.
    4. Dong, Liang & Kot, Hung Wan & Lam, Keith S.K. & Liu, Ming, 2022. "Co-skewness and expected return: Evidence from international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    5. Claudio Raddatz & Sergio L. Schmukler & Tomas Williams, 2015. "International Asset Allocations and Capital Flows: The Benchmark Effect," Working Papers 042015, Hong Kong Institute for Monetary Research.
    6. Xue, Wenjun & He, Zhongzhi & Hu, Yu, 2023. "The destabilizing effect of mutual fund herding: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 88(C).
    7. Kelley Bergsma & Danling Jiang, 2016. "Cultural New Year Holidays and Stock Returns around the World," Financial Management, Financial Management Association International, vol. 45(1), pages 3-35, March.
    8. Broman, Markus S., 2020. "Local demand shocks, excess comovement and return predictability," Journal of Banking & Finance, Elsevier, vol. 119(C).
    9. Todea, Alexandru & Petrescu, Daiana Florina, 2021. "Is stock price informativeness shaped by our genes?," Economic Modelling, Elsevier, vol. 103(C).
    10. Wu, Ming & Ohk, Kiyool & Ko, Kwangsoo, 2021. "Does cash-flow news play a better role than discount-rate news? Evidence from global regional stock markets," Journal of International Money and Finance, Elsevier, vol. 110(C).
    11. Lee, Jinsoo & Yu, Bok-Keun, 2018. "What Drives the Stock Market Comovements between Korea and China, Japan and the U.S.?," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 40(1), pages 45-66.

  2. Miguel A. Ferreira & Pedro Santa-Clara, 2008. "Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole," NBER Working Papers 14571, National Bureau of Economic Research, Inc.

    Cited by:

    1. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    2. 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.
    3. 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.
    4. 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.
    5. Laborda, Ricardo & Laborda, Juan, 2017. "Can tree-structured classifiers add value to the investor?," Finance Research Letters, Elsevier, vol. 22(C), pages 211-226.
    6. 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.
    7. Han, Liyan & Xu, Yang & Yin, Libo, 2017. "Does investor attention matter? The attention-return relation in gold futures market," Economics Discussion Papers 2017-37, Kiel Institute for the World Economy (IfW Kiel).
    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. 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).
    10. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2019. "Structural instability and predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    11. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    12. 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.
    13. 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.
    14. Lee Tae-Hwy & Wang He & Xi Zhou & Zhang Ru, 2023. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 57-83, January.
    15. Olkhov, Victor, 2023. "The Market-Based Probability of Stock Returns," MPRA Paper 116234, University Library of Munich, Germany.
    16. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2023. "Panel Data Nowcasting: The Case of Price-Earnings Ratios," Papers 2307.02673, arXiv.org.
    17. Dooruj McRambaccussing, 2015. "Moment Matching in the Present Value identity, and a New Model," Dundee Discussion Papers in Economics 291, Economic Studies, University of Dundee.
    18. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    19. 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).
    20. Dr. Thomas Nitschka, 2012. "Global and country-specific business cycle risk in time-varying excess returns on asset markets," Working Papers 2012-10, Swiss National Bank.
    21. 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.
    22. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    23. 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).
    24. Aloosh, Arash, 2014. "Global Variance Risk Premium and Forex Return Predictability," MPRA Paper 59931, University Library of Munich, Germany.
    25. 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.
    26. 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.
    27. 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.
    28. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
    29. Taylor, Mark, 2014. "Common Macro Factors and Currency Premia," CEPR Discussion Papers 10016, C.E.P.R. Discussion Papers.
    30. Avino, Davide & Nneji, Ogonna, 2012. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," MPRA Paper 42848, University Library of Munich, Germany.
    31. 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).
    32. Gao, Lei & Han, Yufeng & Zhengzi Li, Sophia & Zhou, Guofu, 2018. "Market intraday momentum," Journal of Financial Economics, Elsevier, vol. 129(2), pages 394-414.
    33. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    34. 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.
    35. Rebecca M. Baker & Tahani Coolen-Maturi & Frank P. A. Coolen, 2017. "Nonparametric predictive inference for stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1333-1349, June.
    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. 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.
    38. 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.
    39. Adam Zaremba, 2019. "The Cross Section of Country Equity Returns: A Review of Empirical Literature," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    40. Cao, Zhen & Han, Liyan & Wei, Xinbei & Zhang, Qunzi, 2022. "Fear in commodity return prediction," Finance Research Letters, Elsevier, vol. 46(PB).
    41. 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).
    42. 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.
    43. 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.
    44. Chue, Timothy K. & Xu, Jin Karen, 2022. "Profitability, asset investment, and aggregate stock returns," Journal of Banking & Finance, Elsevier, vol. 143(C).
    45. 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.
    46. 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.
    47. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    48. 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.
    49. 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.
    50. 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.
    51. Marcelo C. Medeiros & Eduardo F. Mendes, 2012. "Estimating High-Dimensional Time Series Models," CREATES Research Papers 2012-37, Department of Economics and Business Economics, Aarhus University.
    52. 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.
    53. Stephan Kessler & Bernd Scherer, 2013. "Momentum and macroeconomic state variables," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(4), pages 335-363, December.
    54. Shailesh Rana & William H. Bommer & G. Michael Phillips, 2020. "Predicting Returns for Growth and Value Stocks: A Forecast Assessment Approach Using Global Asset Pricing Models," International Journal of Economics and Financial Issues, Econjournals, vol. 10(4), pages 88-106.
    55. Cao, Zhen & Han, Liyan & Zhang, Qunzi, 2022. "Stock return predictability in China: Power of oil price trend," Finance Research Letters, Elsevier, vol. 47(PA).
    56. 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.
    57. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
    58. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
    59. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    60. Qi Zhao, 2020. "A Deep Learning Framework for Predicting Digital Asset Price Movement from Trade-by-trade Data," Papers 2010.07404, arXiv.org.
    61. Qingjie Zhou & Panpan Zhu & Yinpeng Zhang, 2023. "Contagion Spillover from Bitcoin to Carbon Futures Pricing: Perspective from Investor Attention," Energies, MDPI, vol. 16(2), pages 1-22, January.
    62. 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.
    63. 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).
    64. 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.
    65. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    66. Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
    67. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
    68. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    69. 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.
    70. Bai, Jennie & Bali, Turan G. & Wen, Quan, 2021. "Is there a risk-return tradeoff in the corporate bond market? Time-series and cross-sectional evidence," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1017-1037.
    71. 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.
    72. 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.
    73. 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.
    74. 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.
    75. 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).
    76. 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).
    77. 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.
    78. 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.
    79. 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.
    80. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    81. Michael W. McCracken & Giorgio Valente, 2012. "Asymptotic Inference for Performance Fees and the Predictability of Asset Returns," Working Papers 2012-049, Federal Reserve Bank of St. Louis.
    82. Harald Kinateder & Vassilios G. Papavassiliou, 2019. "Sovereign bond return prediction with realized higher moments," Open Access publications 10197/11286, Research Repository, University College Dublin.
    83. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    84. 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.
    85. 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.
    86. 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.
    87. 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.
    88. Ha, Youngmin & Zhang, Hai, 2020. "Algorithmic trading for online portfolio selection under limited market liquidity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1033-1051.
    89. 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).
    90. 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.
    91. 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.
    92. 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).
    93. Tan, Xilong & Tao, Yubo, 2023. "Trend-based forecast of cryptocurrency returns," Economic Modelling, Elsevier, vol. 124(C).
    94. 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.
    95. 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).
    96. 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.
    97. 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).
    98. 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.
    99. 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.
    100. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    101. Lutzenberger, Fabian T., 2014. "The predictability of aggregate returns on commodity futures," Review of Financial Economics, Elsevier, vol. 23(3), pages 120-130.
    102. 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).
    103. 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.
    104. Louis R. Piccotti, 2022. "Portfolio returns and consumption growth covariation in the frequency domain, real economic activity, and expected returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(3), pages 513-549, September.
    105. 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.
    106. Minnick, Kristina & Rosenthal, Leonard, 2014. "Stealth compensation: Do CEOs increase their pay by influencing dividend policy?," Journal of Corporate Finance, Elsevier, vol. 25(C), pages 435-454.
    107. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    108. Wolff, Dominik & Bessler, Wolfgang & Opfer, Heiko, 2012. "Multi-Asset Portfolio Optimization and Out-of-Sample Performance: An Evaluation of Black-Litterman, Mean Variance and Naïve Diversification Approaches," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62020, Verein für Socialpolitik / German Economic Association.
    109. 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.
    110. 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).
    111. 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.
    112. Lin, Hai & Wang, Junbo & Wu, Chunchi, 2014. "Predictions of corporate bond excess returns," Journal of Financial Markets, Elsevier, vol. 21(C), pages 123-152.
    113. 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.
    114. 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).
    115. 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.
    116. Vilkovz, Grigory & Xiaox, Yan, 2013. "Option-implied information and predictability of extreme returns," SAFE Working Paper Series 5, Leibniz Institute for Financial Research SAFE.
    117. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2016. "Intraday return predictability, portfolio maximisation, and hedging," Emerging Markets Review, Elsevier, vol. 28(C), pages 105-116.
    118. Zihao Zhang & Stefan Zohren & Stephen Roberts, 2018. "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books," Papers 1808.03668, arXiv.org, revised Jan 2020.
    119. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    120. 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.
    121. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    122. Andreou, Panayiotis C. & Kagkadis, Anastasios & Philip, Dennis & Taamouti, Abderrahim, 2019. "The information content of forward moments," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 527-541.
    123. 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.
    124. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    125. Manahov, Viktor & Hudson, Robert & Hoque, Hafiz, 2015. "Return predictability and the ‘wisdom of crowds’: Genetic Programming trading algorithms, the Marginal Trader Hypothesis and the Hayek Hypothesis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 85-98.
    126. Les Coleman, 2023. "Explaining mutual fund behavior through the structure‐conduct‐performance lens," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2874-2884, July.
    127. 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).
    128. 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.
    129. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2024. "Panel data nowcasting: The case of price–earnings ratios," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 292-307, March.
    130. Yin, Libo & Yang, Qingyuan, 2016. "Predicting the oil prices: Do technical indicators help?," Energy Economics, Elsevier, vol. 56(C), pages 338-350.
    131. 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.
    132. 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.
    133. 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.
    134. Ngene, Geoffrey M., 2021. "What drives dynamic connectedness of the U.S equity sectors during different business cycles?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    135. 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.
    136. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    137. 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).
    138. Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    139. 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.
    140. 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.
    141. 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.
    142. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    143. Michael Cary, 2020. "Have greenhouse gas emissions from US energy production peaked? State level evidence from six subsectors," Environment Systems and Decisions, Springer, vol. 40(1), pages 125-134, March.
    144. Islam, Raisul & Volkov, Vladimir, 2020. "Calm before the storm: an early warning approach before and during the COVID-19 crisis," Working Papers 2020-09, University of Tasmania, Tasmanian School of Business and Economics.
    145. 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.
    146. Yin, Libo & Feng, Jiabao, 2019. "Can investors attention on oil markets predict stock returns?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 786-800.
    147. 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.
    148. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    149. 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).
    150. 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.
    151. 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.
    152. 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.
    153. 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.
    154. 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.
    155. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    156. Suk Joon Byun & Bart Frijns & Tai‐Yong Roh, 2018. "A comprehensive look at the return predictability of variance risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(4), pages 425-445, April.
    157. 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).
    158. Dou, Winston Wei & Ji, Yan & Wu, Wei, 2021. "Competition, profitability, and discount rates," Journal of Financial Economics, Elsevier, vol. 140(2), pages 582-620.
    159. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.
    160. 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.
    161. 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.
    162. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    163. 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.
    164. 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.
    165. Jacopo Piana & Daniele Bianchi, 2017. "Expected Spot Prices and the Dynamics of Commodity Risk Premia," 2017 Meeting Papers 1149, Society for Economic Dynamics.
    166. Lioui, Abraham & Poncet, Patrice, 2013. "Optimal benchmarking for active portfolio managers," European Journal of Operational Research, Elsevier, vol. 226(2), pages 268-276.
    167. 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.
    168. 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.
    169. 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.
    170. 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).
    171. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    172. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    173. 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.
    174. 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.
    175. 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.
    176. 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.
    177. Eric Jondeau & Michael Rockinger, 2019. "Predicting Long‐Term Financial Returns: VAR versus DSGE Model—A Horse Race," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2239-2291, December.
    178. 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.
    179. Buss, Adrian & Vilkov, Grigory & ,, 2018. "Expected Correlation and Future Market Returns," CEPR Discussion Papers 12760, C.E.P.R. Discussion Papers.
    180. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
    181. Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019. "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    182. Turtle, H.J. & Wang, Kainan, 2016. "The benefits of improved covariance estimation," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 233-246.
    183. 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.

  3. Brandt, Michael W & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns," University of California at Los Angeles, Anderson Graduate School of Management qt4ft420b6, Anderson Graduate School of Management, UCLA.

    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. Miguel Antón & Christopher Polk, 2014. "Connected Stocks," Journal of Finance, American Finance Association, vol. 69(3), pages 1099-1127, June.
    3. Balbás, Alejandro & Laborda Herrero, Ricardo, 2017. "Interest Rate Future Quality Options and Negative Interest Rates," INDEM - Working Paper Business Economic Series 24859, Instituto para el Desarrollo Empresarial (INDEM).
    4. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    5. Laborda, Ricardo & Laborda, Juan, 2017. "Can tree-structured classifiers add value to the investor?," Finance Research Letters, Elsevier, vol. 22(C), pages 211-226.
    6. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    7. Schäfer, Larissa, 2015. "Essays in banking and international finance," Other publications TiSEM 54db9c22-05fa-4444-97d5-1, Tilburg University, School of Economics and Management.
    8. Mohammed Bouaddi & Abderrahim Taamouti, 2012. "Portfolio risk management in a data-rich environment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(4), pages 469-494, December.
    9. Ricardo Laborda & Jose Olmo, 2020. "Optimal portfolio choices using financial leverage," Bulletin of Economic Research, Wiley Blackwell, vol. 72(2), pages 146-166, April.
    10. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2017. "On the gains of using high frequency data and higher moments in Portfolio Selection," CeBER Working Papers 2017-02, Centre for Business and Economics Research (CeBER), University of Coimbra.
    11. Peter Christoffersen & Xuhui (Nick) Pan, 2014. "Equity Portfolio Management Using Option Price Information," CREATES Research Papers 2015-05, Department of Economics and Business Economics, Aarhus University.
    12. Ralph S. J. Koijen & Motohiro Yogo, 2015. "A Demand System Approach to Asset Pricing," Staff Report 510, Federal Reserve Bank of Minneapolis.
    13. Aït-Sahalia, Yacine & Xiu, Dacheng, 2017. "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, vol. 201(2), pages 384-399.
    14. Pedro Barroso & Jurij-Andrei Reichenecker & Marco J. Menichetti, 2022. "Hedging with an Edge: Parametric Currency Overlay," Management Science, INFORMS, vol. 68(1), pages 669-689, January.
    15. Ricardo Laborda & Ramiro Losada, 2017. "Why is investors'mutual fund market allocation far from the optimum?," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    16. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    17. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    18. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Efficient skewness/semivariance portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 331-346, September.
    19. Sait Tunc & Mehmet A. Donmez & Suleyman S. Kozat, 2012. "Optimal Investment Under Transaction Costs," Papers 1203.4153, arXiv.org, revised Jul 2012.
    20. Maio, Paulo, 2013. "Return decomposition and the Intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4958-4972.
    21. Fan, Jianqing & Liao, Yuan & Shi, Xiaofeng, 2013. "Risks of large portfolios," MPRA Paper 44206, University Library of Munich, Germany.
    22. 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.
    23. Ryan T. Ball & Lindsey Gallo & Eric Ghysels, 2019. "Tilting the evidence: the role of firm-level earnings attributes in the relation between aggregated earnings and gross domestic product," Review of Accounting Studies, Springer, vol. 24(2), pages 570-592, June.
    24. 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.
    25. Fuertes, Ana-Maria & Zhao, Nan, 2023. "A Bayesian perspective on commodity style integration," Journal of Commodity Markets, Elsevier, vol. 30(C).
    26. Ammann, Manuel & Coqueret, Guillaume & Schade, Jan-Philip, 2016. "Characteristics-based portfolio choice with leverage constraints," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 23-37.
    27. Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
    28. Yunus Emre Ergemen & Abderrahim Taamouti, 2015. "Parametric Portfolio Policies with Common Volatility Dynamics," CREATES Research Papers 2015-41, Department of Economics and Business Economics, Aarhus University.
    29. 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.
    30. Hong, Harrison & Xu, Jiangmin, 2019. "Inferring latent social networks from stock holdings," Journal of Financial Economics, Elsevier, vol. 131(2), pages 323-344.
    31. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova, 2018. "Exchange rate forecasting and the performance of currency portfolios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 519-540, August.
    32. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joelle, 2021. "The risk premia of energy futures," Energy Economics, Elsevier, vol. 102(C).
    33. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    34. 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.
    35. Juarez-Torres, Miriam & Sanchez, Leonardo & Vedenov, Dmitry V., 2012. "Effectiveness of Weather Derivatives as Cross-Hedging Instrument against Climate Change: The Cases of Reservoir Water Allocation Management in Guanajuato, Mexico," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124813, Agricultural and Applied Economics Association.
    36. Fuertes, Ana-Maria & Zhao, Nan, 2022. "A Bayesian Perspective on Commodity Style Integration," MPRA Paper 117831, University Library of Munich, Germany, revised 2023.
    37. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    38. Adam Farago & Erik Hjalmarsson, 2023. "Small Rebalanced Portfolios Often Beat the Market over Long Horizons," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(2), pages 307-342.
    39. 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).
    40. Meucci, A. & Nicolosi, M., 2016. "Dynamic portfolio management with views at multiple horizons," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 495-518.
    41. Xia, Hui & Min, Xinyu & Deng, Shijie, 2015. "Effectiveness of earnings forecasts in efficient global portfolio construction," International Journal of Forecasting, Elsevier, vol. 31(2), pages 568-574.
    42. Chi-Lin Yang & Jung-Ho Lai, 2021. "Influence of Cross-Listing on the Relationship between Financial Leverage and R&D Investment: A Sustainable Development Strategy," Sustainability, MDPI, vol. 13(18), pages 1-14, September.
    43. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2015. "Efficient Skewness/Semivariance Portfolios," GEMF Working Papers 2015-05, GEMF, Faculty of Economics, University of Coimbra.
    44. Allen, David & Lizieri, Colin & Satchell, Stephen, 2020. "A comparison of non-Gaussian VaR estimation and portfolio construction techniques," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 356-368.
    45. Tony Guida & Guillaume Coqueret, 2019. "Ensemble Learning Applied to Quant Equity: Gradient Boosting in a Multifactor Framework," Post-Print hal-02311104, HAL.
    46. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    47. Guillaume Coqueret & Tony Guida, 2020. "Training trees on tails with applications to portfolio choice," Annals of Operations Research, Springer, vol. 288(1), pages 181-221, May.
    48. Gonzalo, Jesús & Olmo, José, 2016. "Long-term optimal portfolio allocation under dynamic horizon-specific risk aversion," UC3M Working papers. Economics 23599, Universidad Carlos III de Madrid. Departamento de Economía.
    49. 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.
    50. Nikan Firoozye & Vincent Tan & Stefan Zohren, 2022. "Canonical Portfolios: Optimal Asset and Signal Combination," Papers 2202.10817, arXiv.org, revised Jul 2023.
    51. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    52. Kazuhiro Hiraki & George Skiadopoulos, 2023. "The Contribution of Transaction Costs to Expected Stock Returns: A Novel Measure," Working Papers 946, Queen Mary University of London, School of Economics and Finance.
    53. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    54. 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.
    55. Hjalmarsson, Erik & Manchev, Petar, 2012. "Characteristic-based mean-variance portfolio choice," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1392-1401.
    56. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
    57. Uppal, Raman & DeMiguel, Victor & Plyakha, Yuliya & Vilkov, Grigory, 2010. "Improving Portfolio Selection Using Option-Implied Volatility and Skewness," CEPR Discussion Papers 7686, C.E.P.R. Discussion Papers.
    58. Christopher G. Lamoureux & Huacheng Zhang, 2021. "An Empirical Assessment of Characteristics and Optimal Portfolios," Papers 2104.12975, arXiv.org, revised Feb 2024.
    59. Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
    60. Laborda, Ricardo & Muñoz, Fernando, 2016. "Optimal allocation of government bond funds through the business cycle. Is money smart?," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 46-67.
    61. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2020. "Can Volatility Solve the Naive Portfolio Puzzle?," Papers 2005.03204, arXiv.org, revised Feb 2022.
    62. Eric Andr'e & Guillaume Coqueret, 2020. "Dirichlet policies for reinforced factor portfolios," Papers 2011.05381, arXiv.org, revised Jun 2021.
    63. Zaremba, Adam & Andreu, Laura, 2018. "Paper profits or real money? Trading costs and stock market anomalies in country ETFs," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 181-192.
    64. Sanne de Boer, 2010. "Factor tilting for expected utility maximization," Journal of Asset Management, Palgrave Macmillan, vol. 11(1), pages 31-42, April.
    65. 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.
    66. Moura, Guilherme V. & Santos, André A. P. & Ruiz Ortega, Esther, 2019. "Comparing Forecasts of Extremely Large Conditional Covariance Matrices," DES - Working Papers. Statistics and Econometrics. WS 29291, Universidad Carlos III de Madrid. Departamento de Estadística.
    67. Marcelo C. Medeiros & Artur M. Passos & Gabriel F. R. Vasconcelos, 2014. "Parametric Portfolio Selection: Evaluating and Comparing to Markowitz Portfolios," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(2), pages 257-284.
    68. Schüssler, Rainer & Beckmann, Joscha & Koop, Gary & Korobilis, Dimitris, 2018. "Exchange rate predictability and dynamic Bayesian learning," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181523, Verein für Socialpolitik / German Economic Association.
    69. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," LIDAM Reprints LFIN 2021005, Université catholique de Louvain, Louvain Finance (LFIN).
    70. Joachim Inkmann & Zhen Shi, 2015. "Parametric Portfolio Policies in the Surplus Consumption Ratio," International Review of Finance, International Review of Finance Ltd., vol. 15(2), pages 257-282, June.
    71. Simon, Frederik & Weibels, Sebastian & Zimmermann, Tom, 2023. "Deep parametric portfolio policies," CFR Working Papers 23-01, University of Cologne, Centre for Financial Research (CFR).
    72. 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.
    73. Guillaume Chevalier & Guillaume Coqueret & Thomas Raffinot, 2022. "Supervised portfolios," Post-Print hal-04144588, HAL.
    74. De Santis, Roberto A. & Lührmann, Melanie, 2009. "On the determinants of net international portfolio flows: A global perspective," Journal of International Money and Finance, Elsevier, vol. 28(5), pages 880-901, September.
    75. 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).
    76. Daniel Giamouridis & Athanasios Sakkas & Nikolaos Tessaromatis, 2017. "Dynamic Asset Allocation with Liabilities," European Financial Management, European Financial Management Association, vol. 23(2), pages 254-291, March.
    77. Xu, Qifa & Li, Mengting & Jiang, Cuixia, 2021. "Network-augmented time-varying parametric portfolio selection: Evidence from the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    78. Beber, Alessandro & Brandt, Michael W. & Cen, Jason & Kavajecz, Kenneth A., 2021. "Mutual fund performance: Using bespoke benchmarks to disentangle mandates, constraints and skill," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 74-93.
    79. Choi, Jin Ho & Suh, Sangwon, 2021. "A filtered currency carry trade," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    80. Reza Bradrania & Davood Pirayesh Neghab, 2022. "State-dependent Asset Allocation Using Neural Networks," Papers 2211.00871, arXiv.org.
    81. Takano, Yuichi & Gotoh, Jun-ya, 2023. "Dynamic portfolio selection with linear control policies for coherent risk minimization," Operations Research Perspectives, Elsevier, vol. 10(C).
    82. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2015. "Portfolio Management With Higher Moments: The Cardinality Impact," GEMF Working Papers 2015-15, GEMF, Faculty of Economics, University of Coimbra.
    83. Xavier Gerard & Ron Guido & Peter Wesselius, 2013. "Integrated alpha modelling," Journal of Asset Management, Palgrave Macmillan, vol. 14(3), pages 140-161, June.
    84. Laborda, Juan & Laborda, Ricardo & Olmo, Jose, 2014. "Optimal currency carry trade strategies," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 52-66.
    85. Fischer, Marcel & Gallmeyer, Michael F., 2016. "Heuristic portfolio trading rules with capital gain taxes," Journal of Financial Economics, Elsevier, vol. 119(3), pages 611-625.
    86. Ruchika Sehgal & Aparna Mehra, 2023. "Quantile Regression Based Enhanced Indexing with Portfolio Rebalancing," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 721-742, September.
    87. Johannes Bock, 2018. "An updated review of (sub-)optimal diversification models," Papers 1811.08255, arXiv.org.
    88. Moorman, Theodore, 2014. "An empirical investigation of methods to reduce transaction costs," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 230-246.
    89. Trung H. Le & Apostolos Kourtis & Raphael Markellos, 2023. "Modeling skewness in portfolio choice," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 734-770, June.
    90. Gehrig, Thomas & Sögner, Leopold & Westerkamp, Arne, 2018. "Making Parametric Portfolio Policies Work," CEPR Discussion Papers 13193, C.E.P.R. Discussion Papers.
    91. Vilkovz, Grigory & Xiaox, Yan, 2013. "Option-implied information and predictability of extreme returns," SAFE Working Paper Series 5, Leibniz Institute for Financial Research SAFE.
    92. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    93. N'Golo Kone, 2021. "Efficient mean-variance portfolio selection by double regularization," Working Paper 1453, Economics Department, Queen's University.
    94. De Santis, Roberto A. & Lührmann, Melanie, 2006. "On the determinants of external imbalances and net international portfolio flows: a global perspective," Working Paper Series 651, European Central Bank.
    95. Joenväärä, Juha & Kauppila, Mikko & Kahra, Hannu, 2021. "Hedge fund portfolio selection with fund characteristics," Journal of Banking & Finance, Elsevier, vol. 132(C).
    96. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    97. Carter Davis, 2023. "The Elasticity of Quantitative Investment," Papers 2303.14533, arXiv.org.
    98. Valentin Haddad & Serhiy Kozak & Shrihari Santosh & Stijn Van Nieuwerburgh, 2020. "Factor Timing," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 1980-2018.
    99. Chen, Xin & Yang, Dan & Xu, Yan & Xia, Yin & Wang, Dong & Shen, Haipeng, 2023. "Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data," Journal of Econometrics, Elsevier, vol. 232(2), pages 544-564.
    100. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    101. 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.
    102. Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    103. 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.
    104. Bradrania, Reza & Pirayesh Neghab, Davood, 2021. "State-dependent asset allocation using neural networks," MPRA Paper 115254, University Library of Munich, Germany.
    105. Le, Trung H., 2021. "International portfolio allocation: The role of conditional higher moments," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 33-57.
    106. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    107. Laborda, Ricardo & Olmo, Jose, 2017. "Optimal asset allocation for strategic investors," International Journal of Forecasting, Elsevier, vol. 33(4), pages 970-987.
    108. Auh, Jun Kyung & Cho, Wonho, 2023. "Factor-based portfolio optimization," Economics Letters, Elsevier, vol. 228(C).
    109. Guillaume Coqueret & Tony Guida, 2020. "Training trees on tails with applications to portfolio choice," Post-Print hal-04144665, HAL.
    110. 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.
    111. Han, Chulwoo, 2020. "A nonparametric approach to portfolio shrinkage," Journal of Banking & Finance, Elsevier, vol. 120(C).
    112. Vasyl Golosnoy & Benno Hildebrandt & Steffen Köhler, 2019. "Modeling and Forecasting Realized Portfolio Diversification Benefits," JRFM, MDPI, vol. 12(3), pages 1-16, July.
    113. Li, Danyang & Zhang, Zhekai & Cerrato, Mario, 2023. "Factor investing and currency portfolio management," International Review of Financial Analysis, Elsevier, vol. 87(C).
    114. Guillaume Coqueret, 2022. "Characteristics-driven returns in equilibrium," Papers 2203.07865, arXiv.org.
    115. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    116. Branikas, Ioannis & Hong, Harrison & Xu, Jiangmin, 2020. "Location choice, portfolio choice," Journal of Financial Economics, Elsevier, vol. 138(1), pages 74-94.
    117. Jean-Marc Le Caillec, 2022. "Hypothesis Testing Fusion for Nonlinearity Detection in Hedge Fund Price Returns," Post-Print hal-03739132, HAL.
    118. Andrea Berardi & Michael Markovich & Alberto Plazzi & Andrea Tamoni, 2021. "Mind the (Convergence) Gap: Bond Predictability Strikes Back!," Management Science, INFORMS, vol. 67(12), pages 7888-7911, December.
    119. 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).
    120. 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.
    121. Ioannis Branikas & Harrison Hong & Jiangmin Xu, 2017. "Location Choice, Portfolio Choice," NBER Working Papers 23040, National Bureau of Economic Research, Inc.
    122. Ardia, David & Boudt, Kris & Wauters, Marjan, 2016. "The economic benefits of market timing the style allocation of characteristic-based portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 38-62.
    123. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J. & Uppal, Raman, 2017. "A Portfolio Perspective on the Multitude of Firm Characteristics," CEPR Discussion Papers 12417, C.E.P.R. Discussion Papers.
    124. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).
    125. Richard Martin & Torsten Schoneborn, 2011. "Mean Reversion Pays, but Costs," Papers 1103.4934, arXiv.org.
    126. Gomes, Pedro & Taamouti, Abderrahim, 2016. "In search of the determinants of European asset market comovements," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 103-117.
    127. 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.
    128. 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.
    129. Fousseni Chabi-Yo & Markus Huggenberger & Florian Weigert, 2019. "Multivariate Crash Risk," Working Papers on Finance 1901, University of St. Gallen, School of Finance.
    130. Sangwon Suh, 2018. "Portfolio Selection using New Factors based on Firm Characteristics," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(1), pages 77-99, March.

  4. Brandt, Michael W. & Santa-Clara, Pedro, 2004. "Dynamic Portfolio Selection by Augmenting the Asset Space," University of California at Los Angeles, Anderson Graduate School of Management qt632436gt, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. John H. Cochrane, 2014. "A Mean-Variance Benchmark for Intertemporal Portfolio Theory," Journal of Finance, American Finance Association, vol. 69(1), pages 1-49, February.
    2. Caicedo-Llano, Juliana & Dionysopoulos, Thomas, 2008. "Market integration: A risk-budgeting guide for pure alpha investors," Journal of Multinational Financial Management, Elsevier, vol. 18(4), pages 313-327, October.
    3. Bouaddi, Mohammed & Taamouti, Abderrahim, 2013. "Portfolio selection in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2943-2962.
    4. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2015. "On the exact solution of the multi-period portfolio choice problem for an exponential utility under return predictability," European Journal of Operational Research, Elsevier, vol. 246(2), pages 528-542.
    5. Mohammed Bouaddi & Abderrahim Taamouti, 2012. "Portfolio risk management in a data-rich environment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(4), pages 469-494, December.
    6. Ricardo Laborda & Jose Olmo, 2020. "Optimal portfolio choices using financial leverage," Bulletin of Economic Research, Wiley Blackwell, vol. 72(2), pages 146-166, April.
    7. Sentana, Enrique & Peñaranda, Francisco, 2007. "Duality in Mean-Variance Frontiers with Conditioning Information," CEPR Discussion Papers 6566, C.E.P.R. Discussion Papers.
    8. 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.
    9. K. Triantafyllopoulos, 2012. "Multi‐variate stochastic volatility modelling using Wishart autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 48-60, January.
    10. Dmytro Ivasiuk, 2019. "An approximate solution for the power utility optimization under predictable returns," Papers 1911.06552, arXiv.org, revised Oct 2021.
    11. 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).
    12. 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.
    13. Maio, Paulo, 2013. "Return decomposition and the Intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4958-4972.
    14. 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.
    15. Martin D. D. Evans (Georgetown University) and Viktoria Hnatkovska (Georgetown University), 2005. "Solving General Equilibrium Models with Incomplete Markets and Many Assets," Working Papers gueconwpa~05-05-18, Georgetown University, Department of Economics.
    16. 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).
    17. Andrea Buraschi & Andrea Carnelli, 2013. "The economic value of predictability in portfolio management," Journal of Financial Management, Markets and Institutions, Società editrice il Mulino, issue 1, pages 5-22, January.
    18. I-Hsuan Ethan Chiang, 2016. "Skewness And Coskewness In Bond Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 39(2), pages 145-178, June.
    19. Francisco Peñaranda, 2009. "Understanding portfolio efficiency with conditioning information," Economics Working Papers 1146, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2011.
    20. Michael W. Brandt & Pedro Santa-Clara & Rossen Valkanov, 2009. "Parametric Portfolio Policies: Exploiting Characteristics in the Cross-Section of Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3411-3447, September.
    21. 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.
    22. Gonzalo, Jesús & Olmo, José, 2016. "Long-term optimal portfolio allocation under dynamic horizon-specific risk aversion," UC3M Working papers. Economics 23599, Universidad Carlos III de Madrid. Departamento de Economía.
    23. 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.
    24. Nikan Firoozye & Vincent Tan & Stefan Zohren, 2022. "Canonical Portfolios: Optimal Asset and Signal Combination," Papers 2202.10817, arXiv.org, revised Jul 2023.
    25. Martin Hoesli & Eva Liljeblom & Anders Löflund, 2012. "The Effect of Lock-Ups on the Suggested Real Estate Portfolio Weight," Swiss Finance Institute Research Paper Series 12-22, Swiss Finance Institute.
    26. Hjalmarsson, Erik & Manchev, Petar, 2012. "Characteristic-based mean-variance portfolio choice," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1392-1401.
    27. Wan-Yi Chiu, 2021. "Mean-variance hedging in the presence of estimation risk," Review of Derivatives Research, Springer, vol. 24(3), pages 221-241, October.
    28. 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.
    29. N'Golo Kone, 2020. "A Multi-Period Portfolio Selection in a Large Financial Market," Working Paper 1439, Economics Department, Queen's University.
    30. Gatzert, Nadine & Martin, Alexander & Schmidt, Martin & Seith, Benjamin & Vogl, Nikolai, 2021. "Portfolio optimization with irreversible long-term investments in renewable energy under policy risk: A mixed-integer multistage stochastic model and a moving-horizon approach," European Journal of Operational Research, Elsevier, vol. 290(2), pages 734-748.
    31. Bansal, Ravi & Dahlquist, Magnus & Harvey, Campbell R., 2004. "Dynamic Trading Strategies and Portfolio Choice," SIFR Research Report Series 31, Institute for Financial Research.
    32. Joachim Inkmann & Zhen Shi, 2015. "Parametric Portfolio Policies in the Surplus Consumption Ratio," International Review of Finance, International Review of Finance Ltd., vol. 15(2), pages 257-282, June.
    33. Didier, Tatiana & Lowenkron, Alexandre, 2012. "The current account as a dynamic portfolio choice problem," Journal of the Japanese and International Economies, Elsevier, vol. 26(4), pages 518-541.
    34. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility Function," Papers 1207.1003, arXiv.org, revised Nov 2014.
    35. Maurer, Raimond & Mitchell, Olivia S. & Rogalla, Ralph, 2009. "Managing contribution and capital market risk in a funded public defined benefit plan: Impact of CVaR cost constraints," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 25-34, August.
    36. Miguel A. Ferreira & Pedro Santa-Clara, 2008. "Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole," NBER Working Papers 14571, National Bureau of Economic Research, Inc.
    37. Ralph S.J. Koijen & Otto Van Hemert & Stijn Van Nieuwerburgh, 2007. "Mortgage Timing," NBER Working Papers 13361, National Bureau of Economic Research, Inc.
    38. 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).
    39. Reza Bradrania & Davood Pirayesh Neghab, 2022. "State-dependent Asset Allocation Using Neural Networks," Papers 2211.00871, arXiv.org.
    40. Evans, Martin D.D. & Hnatkovska, Viktoria, 2012. "A method for solving general equilibrium models with incomplete markets and many financial assets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1909-1930.
    41. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2022. "Crypto Asset Portfolio Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
    42. Gehrig, Thomas & Sögner, Leopold & Westerkamp, Arne, 2018. "Making Parametric Portfolio Policies Work," CEPR Discussion Papers 13193, C.E.P.R. Discussion Papers.
    43. 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.
    44. Joenväärä, Juha & Kauppila, Mikko & Kahra, Hannu, 2021. "Hedge fund portfolio selection with fund characteristics," Journal of Banking & Finance, Elsevier, vol. 132(C).
    45. Basak, Suleyman & Chabakauri, Georgy, 2009. "Dynamic Mean-Variance Asset Allocation," CEPR Discussion Papers 7256, C.E.P.R. Discussion Papers.
    46. Chen, Xin & Yang, Dan & Xu, Yan & Xia, Yin & Wang, Dong & Shen, Haipeng, 2023. "Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data," Journal of Econometrics, Elsevier, vol. 232(2), pages 544-564.
    47. Chung, Chris Changwha & Lee, Seung-Hyun & Beamish, Paul W. & Southam, Colette & Nam, Daeil (Dale), 2013. "Pitting real options theory against risk diversification theory: International diversification and joint ownership control in economic crisis," Journal of World Business, Elsevier, vol. 48(1), pages 122-136.
    48. 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.
    49. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    50. Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    51. Chiu, Wan-Yi, 2022. "Stepwise expanding the frontier one asset at a time," Finance Research Letters, Elsevier, vol. 46(PA).
    52. John Powell & Jing Shi & Tom Smith & Robert Whaley, 2009. "Common Divisors, Payout Persistence, and Return Predictability," International Review of Finance, International Review of Finance Ltd., vol. 9(4), pages 335-357, December.
    53. Caio Vigo Pereira, 2020. "Portfolio Efficiency with High-Dimensional Data as Conditioning Information," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202015, University of Kansas, Department of Economics, revised Sep 2020.
    54. Bradrania, Reza & Pirayesh Neghab, Davood, 2021. "State-dependent asset allocation using neural networks," MPRA Paper 115254, University Library of Munich, Germany.
    55. Laborda, Ricardo & Olmo, Jose, 2017. "Optimal asset allocation for strategic investors," International Journal of Forecasting, Elsevier, vol. 33(4), pages 970-987.
    56. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    57. Golosnoy, Vasyl & Okhrin, Yarema, 2009. "Flexible shrinkage in portfolio selection," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 317-328, February.
    58. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.
    59. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wofgang Schmid, 2018. "Mean-Variance Efficiency of Optimal Power and Logarithmic Utility Portfolios," Papers 1806.08005, arXiv.org, revised May 2019.
    60. Jean-Marc Le Caillec, 2022. "Hypothesis Testing Fusion for Nonlinearity Detection in Hedge Fund Price Returns," Post-Print hal-03739132, HAL.
    61. Andrea Berardi & Michael Markovich & Alberto Plazzi & Andrea Tamoni, 2021. "Mind the (Convergence) Gap: Bond Predictability Strikes Back!," Management Science, INFORMS, vol. 67(12), pages 7888-7911, December.
    62. 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.
    63. 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.
    64. Bhaduri, Saumitra & Saraogi, Ravi, 2010. "The predictive power of the yield spread in timing the stock market," Emerging Markets Review, Elsevier, vol. 11(3), pages 261-272, September.
    65. Peñaranda, Francisco, 2009. "Understanding portfolio efficiency with conditioning information," LSE Research Online Documents on Economics 24415, London School of Economics and Political Science, LSE Library.
    66. Gomes, Pedro & Taamouti, Abderrahim, 2016. "In search of the determinants of European asset market comovements," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 103-117.

  5. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan Storud, 2004. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," NBER Working Papers 10934, National Bureau of Economic Research, Inc.

    Cited by:

    1. 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.
    2. Mark Broadie & Weiwei Shen, 2016. "High-Dimensional Portfolio Optimization With Transaction Costs," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-49, June.
    3. Cong, F. & Oosterlee, C.W., 2016. "Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 64(C), pages 23-38.
    4. Lorenzo Garlappi & Georgios Skoulakis, 2009. "Numerical Solutions to Dynamic Portfolio Problems: The Case for Value Function Iteration using Taylor Approximation," Computational Economics, Springer;Society for Computational Economics, vol. 33(2), pages 193-207, March.
    5. Escobar-Anel, Marcos & Havrylenko, Yevhen & Kschonnek, Michel & Zagst, Rudi, 2022. "Decrease of capital guarantees in life insurance products: Can reinsurance stop it?," Insurance: Mathematics and Economics, Elsevier, vol. 105(C), pages 14-40.
    6. Vilkkumaa, Eeva & Liesiö, Juuso & Salo, Ahti, 2014. "Optimal strategies for selecting project portfolios using uncertain value estimates," European Journal of Operational Research, Elsevier, vol. 233(3), pages 772-783.
    7. Zhu, Yichen & Escobar-Anel, Marcos, 2022. "Polynomial affine approach to HARA utility maximization with applications to OrnsteinUhlenbeck 4/2 models," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    8. Redouane Elkamhia & Denitsa Stefanova, 2011. "Dynamic Correlation or Tail Dependence Hedging for Portfolio Selection," Tinbergen Institute Discussion Papers 11-028/2/DSF10, Tinbergen Institute.
    9. Uppal, Raman & Vilkov, Grigory & Buss, Adrian, 2015. "Where Experience Matters: Asset Allocation and Asset Pricing with Opaque and Illiquid Assets," CEPR Discussion Papers 10437, C.E.P.R. Discussion Papers.
    10. Chen, Yu-Wang & Poon, Ser-Huang & Yang, Jian-Bo & Xu, Dong-Ling & Zhang, Dongxu & Acomb, Simon, 2012. "Belief rule-based system for portfolio optimisation with nonlinear cash-flows and constraints," European Journal of Operational Research, Elsevier, vol. 223(3), pages 775-784.
    11. Carlos Heitor Campania & René Garcia, 2019. "Approximate analytical solutions for consumption/investment problems under recursive utility and finite horizon," Post-Print hal-02894663, HAL.
    12. Najafi, Amir Abbas & Pourahmadi, Zahra, 2016. "An efficient heuristic method for dynamic portfolio selection problem under transaction costs and uncertain conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 154-162.
    13. Escobar-Anel, Marcos & Gollart, Maximilian & Zagst, Rudi, 2022. "Closed-form portfolio optimization under GARCH models," Operations Research Perspectives, Elsevier, vol. 9(C).
    14. Paul Ehling & Michael Gallmeyer & Sanjay Srivastava & Stathis Tompaidis & Chunyu Yang, 2018. "Portfolio Tax Trading with Carryover Losses," Management Science, INFORMS, vol. 64(9), pages 4156-4176, September.
    15. Kasper Larsen & Oleksii Mostovyi & Gordan Žitković, 2018. "An expansion in the model space in the context of utility maximization," Finance and Stochastics, Springer, vol. 22(2), pages 297-326, April.
    16. Franc{c}ois Legendre & Djibril Togola, 2015. "Explicit solution to dynamic portfolio choice problem : The continuous-time detour," Papers 1504.03079, arXiv.org.
    17. Dmytro Ivasiuk, 2019. "An approximate solution for the power utility optimization under predictable returns," Papers 1911.06552, arXiv.org, revised Oct 2021.
    18. Mathias S. Kruttli, 2016. "From Which Consumption-Based Asset Pricing Models Can Investors Profit? Evidence from Model-Based Priors," Finance and Economics Discussion Series 2016-027, Board of Governors of the Federal Reserve System (U.S.).
    19. Markus Haas, 2007. "Do investors dislike kurtosis?," Economics Bulletin, AccessEcon, vol. 7(2), pages 1-9.
    20. Marekwica, Marcel, 2012. "Optimal tax-timing and asset allocation when tax rebates on capital losses are limited," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2048-2063.
    21. Joachim Inkmann & David Blake & Zhen Shi, 2017. "Managing Financially Distressed Pension Plans In The Interest Of Beneficiaries," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(2), pages 539-565, June.
    22. Chen, D.H.J. & Beetsma, R.M.W.J. & van Wijnbergen, S.J.G., 2020. "Unhedgeable inflation risk within pension schemes," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 7-24.
    23. Jérôme Detemple, 2014. "Portfolio Selection: A Review," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 1-21, April.
    24. Yichen Zhu & Marcos Escobar-Anel & Matt Davison, 2023. "A Polynomial-Affine Approximation for Dynamic Portfolio Choice," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1177-1213, October.
    25. Mehlkopf, R.J., 2011. "Risk sharing with the unborn," Other publications TiSEM fe8a8df6-455f-4624-af10-9, Tilburg University, School of Economics and Management.
    26. Nalpas, Nicolas & Simar, Léopold & Vanhems, Anne, 2016. "Portfolio Selection in a Multi-Input Multi-Output Setting: a Simple Monte-Carlo-FDH Algorithm," TSE Working Papers 16-648, Toulouse School of Economics (TSE).
    27. Vahidreza Yousefi & Siamak Haji Yakhchali & Jolanta Tamošaitienė, 2019. "Application of Duration Measure in Quantifying the Sensitivity of Project Returns to Changes in Discount Rates," Administrative Sciences, MDPI, vol. 9(1), pages 1-14, February.
    28. Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
    29. Ma, Guiyuan & Siu, Chi Chung & Zhu, Song-Ping, 2022. "Portfolio choice with return predictability and small trading frictions," Economic Modelling, Elsevier, vol. 111(C).
    30. Martin D. D. Evans (Georgetown University) and Viktoria Hnatkovska (Georgetown University), 2005. "Solving General Equilibrium Models with Incomplete Markets and Many Assets," Working Papers gueconwpa~05-05-18, Georgetown University, Department of Economics.
    31. Tao Chen & Michael Ludkovski, 2019. "A Machine Learning Approach to Adaptive Robust Utility Maximization and Hedging," Papers 1912.00244, arXiv.org, revised May 2020.
    32. Peijnenburg, Kim, 2018. "Life-Cycle Asset Allocation with Ambiguity Aversion and Learning," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(5), pages 1963-1994, October.
    33. Peijnenburg, J.M.J. & Nijman, T.E. & Werker, B.J.M., 2010. "Optimal Annuitization with Incomplete Annuity Markets and Background Risk During Retirement," Discussion Paper 2010-11, Tilburg University, Center for Economic Research.
    34. Martin B. Haugh & Leonid Kogan & Jiang Wang, 2006. "Evaluating Portfolio Policies: A Duality Approach," Operations Research, INFORMS, vol. 54(3), pages 405-418, June.
    35. Jessica A. Wachter & Missaka Warusawitharana, 2011. "What is the Chance that the Equity Premium Varies over Time? Evidence from Regressions on the Dividend-Price Ratio," NBER Working Papers 17334, National Bureau of Economic Research, Inc.
    36. Björn Bick & Holger Kraft & Claus Munk, 2013. "Solving Constrained Consumption-Investment Problems by Simulation of Artificial Market Strategies," Management Science, INFORMS, vol. 59(2), pages 485-503, June.
    37. Wouterse, B.; & Hussem, A.; & Wong, A.;, 2018. "The effect of co-payments in Long Term Care on the distribution of payments,consumption, and risk," Health, Econometrics and Data Group (HEDG) Working Papers 18/24, HEDG, c/o Department of Economics, University of York.
    38. Monika Bütler & Kim Peijnenburg & Stefan Staubli, 2013. "How Much Do Means-Tested Benefits Reduce the Demand for Annuities?," NRN working papers 2013-11, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    39. Jules Binsbergen & Michael Brandt, 2007. "Solving dynamic portfolio choice problems by recursing on optimized portfolio weights or on the value function?," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 355-367, May.
    40. Thomas Breuer & Martin Jandačka, 2008. "Portfolio selection with transaction costs under expected shortfall constraints," Computational Management Science, Springer, vol. 5(4), pages 305-316, October.
    41. Davide Pettenuzzo & Allan G. Timmermann & Rossen I. Valkanov, 2008. "Return Predictability under Equilibrium Constraints on the Equity Premium," Working Papers 37, Brandeis University, Department of Economics and International Business School.
    42. Shuo Cao, 2018. "Learning about Term Structure Predictability under Uncertainty," GRU Working Paper Series GRU_2018_006, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    43. Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
    44. Hui Chen & Nengjiu Ju & Jianjun Miao, 2014. "Dynamic Asset Allocation with Ambiguous Return Predictability," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(4), pages 799-823, October.
    45. Michael Johannes & Arthur Korteweg & Nicholas Polson, 2014. "Sequential Learning, Predictability, and Optimal Portfolio Returns," Journal of Finance, American Finance Association, vol. 69(2), pages 611-644, April.
    46. Jessica A. Wachter & Missaka Warusawitharana, 2006. "Predictable returns and asset allocation: Should a skeptical investor time the market?," 2006 Meeting Papers 22, Society for Economic Dynamics.
    47. Geoffrey J. Warren, 2008. "Implications for Asset Pricing Puzzles of a Roll‐over Assumption for the Risk‐Free Asset," International Review of Finance, International Review of Finance Ltd., vol. 8(3‐4), pages 125-157, September.
    48. Engsted, Tom & Pedersen, Thomas Q., 2012. "Return predictability and intertemporal asset allocation: Evidence from a bias-adjusted VAR model," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 241-253.
    49. Roche, Hervé & Tompaidis, Stathis & Yang, Chunyu, 2013. "Why does junior put all his eggs in one basket? A potential rational explanation for holding concentrated portfolios," Journal of Financial Economics, Elsevier, vol. 109(3), pages 775-796.
    50. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
    51. Jessica Wachter, 2010. "Asset Allocation," NBER Working Papers 16255, National Bureau of Economic Research, Inc.
    52. León, Angel & Vaello-Sebastià, Antoni, 2010. "A simulation-based algorithm for American executive stock option valuation," Finance Research Letters, Elsevier, vol. 7(1), pages 14-23, March.
    53. Costanza Torricelli, 2009. "Models For Household Portfolios And Life-Cycle Allocations In The Presence Of Labour Income And Longevity Risk," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0017, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    54. Kaminski, Kathryn & Lo, Andrew W., 2008. "When Do Stop-Loss Rules Stop Losses?," SIFR Research Report Series 63, Institute for Financial Research.
    55. Fischer, Marcel & Kraft, Holger & Munk, Claus, 2013. "Asset allocation over the life cycle: How much do taxes matter?," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2217-2240.
    56. Zhou, Chunyang & Wu, Chongfeng & Wang, Yudong, 2019. "Dynamic portfolio allocation with time-varying jump risk," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 113-124.
    57. Ikefuji, M. & Laeven, R.J.A. & Magnus, J.R. & Muris, C.H.M., 2010. "Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model," Other publications TiSEM 52cbee73-e1dc-4ed3-8ec9-6, Tilburg University, School of Economics and Management.
    58. Yichen Zhu & Marcos Escobar-Anel, 2021. "A Neural Network Monte Carlo Approximation for Expected Utility Theory," JRFM, MDPI, vol. 14(7), pages 1-18, July.
    59. Campbell, John Y & Viceira, Luis, 2005. "The Term Structure of the Risk-Return Tradeoff," CEPR Discussion Papers 4914, C.E.P.R. Discussion Papers.
    60. Farina Weiss, 2021. "A numerical approach to solve consumption-portfolio problems with predictability in income, stock prices, and house prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 93(1), pages 33-81, February.
    61. Kasper Larsen & Oleksii Mostovyi & Gordan v{Z}itkovi'c, 2014. "An expansion in the model space in the context of utility maximization," Papers 1410.0946, arXiv.org, revised Aug 2016.
    62. Rongju Zhang & Nicolas Langren'e & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2018. "Local Control Regression: Improving the Least Squares Monte Carlo Method for Portfolio Optimization," Papers 1803.11467, arXiv.org, revised Sep 2018.
    63. Fahrenwaldt, Matthias A. & Sun, Chaofan, 2020. "Expected utility approximation and portfolio optimisation," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 301-314.
    64. Peijnenburg, Kim & Nijman, Theo & Werker, Bas J.M., 2016. "The annuity puzzle remains a puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 18-35.
    65. Zhang, Yugui & Zhu, Jie & Zhu, Xiaoneng, 2020. "Investing for the long run when expected equity premium is nonnegative," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    66. Kent Smetters & Xingtan Zhang, 2013. "A Sharper Ratio: A General Measure for Correctly Ranking Non-Normal Investment Risks," NBER Working Papers 19500, National Bureau of Economic Research, Inc.
    67. 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.
    68. Rongju Zhang & Nicolas Langren'e & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2016. "Dynamic portfolio optimization with liquidity cost and market impact: a simulation-and-regression approach," Papers 1610.07694, arXiv.org, revised Jun 2019.
    69. Ralph S. J. Koijen & Juan Carlos Rodríguez & Alessandro Sbuelz, 2009. "Momentum and Mean Reversion in Strategic Asset Allocation," Management Science, INFORMS, vol. 55(7), pages 1199-1213, July.
    70. Thorsten Hens & Peter Wöhrmann, 2007. "Strategic asset allocation and market timing: a reinforcement learning approach," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 369-381, May.
    71. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2005. "Portfolio Choice over the Life-Cycle in the Presence of 'Trickle Down' Labor Income," NBER Working Papers 11247, National Bureau of Economic Research, Inc.
    72. Mark E. Wohar & David E. Rapach, 2005. "Return Predictability and the Implied Intertemporal Hedging Demands for Stocks and Bonds: International Evidence," Computing in Economics and Finance 2005 329, Society for Computational Economics.
    73. Yi-Min Chen & Feng-Jyh Lin, 2013. "Do financially innovative futures matter?," The Service Industries Journal, Taylor & Francis Journals, vol. 33(9-10), pages 941-957, July.
    74. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility Function," Papers 1207.1003, arXiv.org, revised Nov 2014.
    75. David Feldman, 2007. "Incomplete information equilibria: Separation theorems and other myths," Annals of Operations Research, Springer, vol. 151(1), pages 119-149, April.
    76. Bram Wouterse & Arjen Hussem, 2019. "The welfare effects of co-payments in long term care," CPB Discussion Paper 394, CPB Netherlands Bureau for Economic Policy Analysis.
    77. Arkadiy V. Sakhartov, 2017. "Economies of Scope, Resource Relatedness, and the Dynamics of Corporate Diversification," Strategic Management Journal, Wiley Blackwell, vol. 38(11), pages 2168-2188, November.
    78. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2007. "Portfolio choice over the life-cycle when the stock and labor markets are cointegrated," Working Paper Series WP-07-11, Federal Reserve Bank of Chicago.
    79. Robert Ferstl & Alex Weissensteiner, 2010. "Backtesting short-term treasury management strategies based on multi-stage stochastic programming," Journal of Asset Management, Palgrave Macmillan, vol. 11(2), pages 94-112, June.
    80. Ferstl, Robert & Weissensteiner, Alex, 2011. "Asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 182-192, January.
    81. Daniel Giamouridis & Athanasios Sakkas & Nikolaos Tessaromatis, 2017. "Dynamic Asset Allocation with Liabilities," European Financial Management, European Financial Management Association, vol. 23(2), pages 254-291, March.
    82. Kamma, Thijs & Pelsser, Antoon, 2022. "Near-optimal asset allocation in financial markets with trading constraints," European Journal of Operational Research, Elsevier, vol. 297(2), pages 766-781.
    83. Areski Cousin & Ying Jiao & Christian y Robert & Olivier David Zerbib, 2021. "Optimal asset allocation subject to withdrawal risk and solvency constraints," Working Papers hal-03244380, HAL.
    84. Simon Lysbjerg Hansen, 2005. "A Malliavin-based Monte-Carlo Approach for Numerical Solution of Stochastic Control Problems: Experiences from Merton's Problem," Computing in Economics and Finance 2005 391, Society for Computational Economics.
    85. Christian Bender & Nikolaus Schweizer, 2019. "`Regression Anytime' with Brute-Force SVD Truncation," Papers 1908.08264, arXiv.org, revised Oct 2020.
    86. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Mean-variance dynamic portfolio allocation with transaction costs: a Wiener chaos expansion approach," Working Papers hal-04086378, HAL.
    87. Gülpinar, Nalan & Pachamanova, Dessislava, 2013. "A robust optimization approach to asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2031-2041.
    88. Rongju Zhang & Nicolas Langrené & Yu Tian & Zili Zhu & Fima Klebaner & Kais Hamza, 2019. "Skewed target range strategy for multiperiod portfolio optimization using a two-stage least squares Monte Carlo method," Post-Print hal-02909342, HAL.
    89. Evans, Martin D.D. & Hnatkovska, Viktoria, 2012. "A method for solving general equilibrium models with incomplete markets and many financial assets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1909-1930.
    90. Alois Geyer & Michael Hanke & Alex Weissensteiner, 2009. "A stochastic programming approach for multi-period portfolio optimization," Computational Management Science, Springer, vol. 6(2), pages 187-208, May.
    91. Shanken, Jay & Tamayo, Ane, 2012. "Payout yield, risk, and mispricing: A Bayesian analysis," Journal of Financial Economics, Elsevier, vol. 105(1), pages 131-152.
    92. Marekwica, Marcel & Schaefer, Alexander & Sebastian, Steffen, 2013. "Life cycle asset allocation in the presence of housing and tax-deferred investing," Journal of Economic Dynamics and Control, Elsevier, vol. 37(6), pages 1110-1125.
    93. Ehsan Hajizadeh & Masoud Mahootchi, 2019. "Developing a Risk-Based Approach for American Basket Option Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1593-1612, April.
    94. Ludkovski, Michael, 2009. "A simulation approach to optimal stopping under partial information," Stochastic Processes and their Applications, Elsevier, vol. 119(12), pages 4061-4087, December.
    95. 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.
    96. Peijnenburg, J.M.J. & Nijman, T.E. & Werker, B.J.M., 2010. "Health Cost Risk and Optimal Retirement Provision : A Simple Rule for Annuity Demand," Other publications TiSEM f178a33d-4386-4036-861f-6, Tilburg University, School of Economics and Management.
    97. Veronesi, Pietro & Pástor, Luboš, 2009. "Learning in Financial Markets," CEPR Discussion Papers 7127, C.E.P.R. Discussion Papers.
    98. Agnieszka Karolina Konicz & David Pisinger & Alex Weissensteiner, 2016. "Optimal retirement planning with a focus on single and joint life annuities," Quantitative Finance, Taylor & Francis Journals, vol. 16(2), pages 275-295, February.
    99. Anne Pedersen & Alex Weissensteiner & Rolf Poulsen, 2013. "Financial planning for young households," Annals of Operations Research, Springer, vol. 205(1), pages 55-76, May.
    100. Mark Broadie & Weiwei Shen, 2017. "Numerical solutions to dynamic portfolio problems with upper bounds," Computational Management Science, Springer, vol. 14(2), pages 215-227, April.
    101. Thijs Kamma & Antoon Pelsser, 2019. "Near-Optimal Dynamic Asset Allocation in Financial Markets with Trading Constraints," Papers 1906.12317, arXiv.org, revised Oct 2019.
    102. Trino-Manuel Niguez & Ivan Paya & David Peel & Javier Perote, 2013. "Higher-order moments in the theory of diversification and portfolio composition," Working Papers 18297128, Lancaster University Management School, Economics Department.
    103. Basak, Suleyman & Chabakauri, Georgy, 2009. "Dynamic Mean-Variance Asset Allocation," CEPR Discussion Papers 7256, C.E.P.R. Discussion Papers.
    104. Bart Diris & Franz Palm & Peter Schotman, 2015. "Long-Term Strategic Asset Allocation: An Out-of-Sample Evaluation," Management Science, INFORMS, vol. 61(9), pages 2185-2202, September.
    105. Roy P. P. M. Hoevenaars & Roderick D. J. Molenaar & Peter C. Schotman & Tom B. M. Steenkamp, 2014. "Strategic Asset Allocation For Long‐Term Investors: Parameter Uncertainty And Prior Information," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 353-376, April.
    106. Jessica A. Wachter & Missaka Warusawitharana, 2009. "What is the chance that the equity premium varies over time? evidence from predictive regressions," Finance and Economics Discussion Series 2009-26, Board of Governors of the Federal Reserve System (U.S.).
    107. Bram Wouterse & Arjen Hussem & Albert Wong, 2022. "The risk protection and redistribution effects of long‐term care co‐payments," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(1), pages 161-186, March.
    108. Carlos Castro, 2010. "Portfolio choice under local industry and country factors," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(4), pages 353-393, December.
    109. Jin-Ray Lu & Chih-Ming Chan & Wen-Shen Li, 2011. "Portfolio Selections with Innate Learning Ability," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 10(3), pages 201-217, December.
    110. 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, December.
    111. Branger, Nicole & Larsen, Linda Sandris & Munk, Claus, 2013. "Robust portfolio choice with ambiguity and learning about return predictability," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1397-1411.
    112. Jules H. van Binsbergen & Michael W. Brandt, 2007. "Optimal Asset Allocation in Asset Liability Management," NBER Working Papers 12970, National Bureau of Economic Research, Inc.
    113. Carmona, Julio & León, Ángel & Vaello-Sebastià, Antoni, 2012. "Executive Stock Options and Time Diversification," QM&ET Working Papers 12-16, University of Alicante, D. Quantitative Methods and Economic Theory.
    114. Koijen, R.S.J. & Nijman, T.E. & Werker, B.J.M., 2006. "Optimal Portfolio Choice with Annuitization," Discussion Paper 2006-78, Tilburg University, Center for Economic Research.
    115. Haixiang Yao & Xun Li & Zhifeng Hao & Yong Li, 2016. "Dynamic asset–liability management in a Markov market with stochastic cash flows," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1575-1597, October.
    116. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.
    117. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wofgang Schmid, 2018. "Mean-Variance Efficiency of Optimal Power and Logarithmic Utility Portfolios," Papers 1806.08005, arXiv.org, revised May 2019.
    118. Koijen, R.S.J. & Nijman, T.E. & Werker, B.J.M., 2006. "Optimal Portfolio Choice with Annuitization," Other publications TiSEM e0ee89d5-4a5f-4c70-a7ee-d, Tilburg University, School of Economics and Management.
    119. Xu, Liang & Gao, Chunyan & Kou, Gang & Liu, Qinjun, 2017. "Comonotonic approximation to periodic investment problems under stochastic drift," European Journal of Operational Research, Elsevier, vol. 262(1), pages 251-261.
    120. Fei Cong & Cornelis W. Oosterlee, 2017. "Accurate and Robust Numerical Methods for the Dynamic Portfolio Management Problem," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 433-458, March.
    121. Tomasz R. Bielecki & Tao Chen & Igor Cialenco & Areski Cousin & Monique Jeanblanc, 2017. "Adaptive Robust Control Under Model Uncertainty," Papers 1706.02227, arXiv.org.
    122. Shao, Adam W. & Chen, Hua & Sherris, Michael, 2019. "To borrow or insure? Long term care costs and the impact of housing," Insurance: Mathematics and Economics, Elsevier, vol. 85(C), pages 15-34.
    123. Boyle, Phelim & Imai, Junichi & Tan, Ken Seng, 2008. "Computation of optimal portfolios using simulation-based dimension reduction," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 327-338, December.
    124. Matt Davison & Marcos Escobar-Anel & Yichen Zhu, 2022. "Optimal market completion through financial derivatives with applications to volatility risk," Papers 2202.08148, arXiv.org.
    125. 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.
    126. Castaneda, Pablo & Rudolph, Heinz P., 2011. "Upgrading investment regulations in second pillar pension systems : a proposal for Colombia," Policy Research Working Paper Series 5775, The World Bank.
    127. Gomes, Francisco & Michaelides, Alexander & Zhang, Yuxin, 2018. "Tactical Target Date Funds," CEPR Discussion Papers 13019, C.E.P.R. Discussion Papers.
    128. Jimmy E. Hilliard & Jitka Hilliard, 2018. "Rebalancing versus buy and hold: theory, simulation and empirical analysis," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 1-32, January.
    129. Jose Faias & Pedro Santa-Clara, 2011. "Optimal Option Portfolio Strategies," EcoMod2011 3041, EcoMod.

  6. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.

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    2. Stylianos Asimakopoulos & Joan Paredes & Thomas Warmedinger, 2020. "Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 369-390, January.
    3. Etienne, Xiaoli, 2015. "Financialization of Agricultural Commodity Markets: Do Financial Data Help to Forecast Agricultural Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 211626, International Association of Agricultural Economists.
    4. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    5. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    6. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    7. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    8. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    9. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    10. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    11. Aharon, David Y. & Qadan, Mahmoud, 2020. "When do retail investors pay attention to their trading platforms?," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    12. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    13. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
    14. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    15. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    16. Byun, Suk Joon & Kim, Jun Sik, 2013. "The information content of risk-neutral skewness for volatility forecasting," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 142-161.
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    18. Özer Karagedikli & Murat Özbilgin, 2019. "Mixed in New Zealand: Nowcasting Labour Markets with MIDAS," Reserve Bank of New Zealand Analytical Notes series AN2019/04, Reserve Bank of New Zealand.
    19. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    20. Christopher F. Baum & Mustafa Caglayan & Oleksandr Talavera, 2006. "On the Sensitivity of Firms' Investment to Cash Flow and Uncertainty," Boston College Working Papers in Economics 638, Boston College Department of Economics, revised 26 Apr 2008.
    21. Lixiong Yang, 2022. "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, vol. 62(2), pages 533-551, February.
    22. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    23. Babii, Andrii & Florens, Jean-Pierre, 2020. "Is completeness necessary? Estimation in nonidentified linear models," TSE Working Papers 20-1091, Toulouse School of Economics (TSE).
    24. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    25. Tsiakas, Ilias & Zhang, Haibin, 2021. "Economic fundamentals and the long-run correlation between exchange rates and commodities," Global Finance Journal, Elsevier, vol. 49(C).
    26. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    27. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    28. C. Emre Alper & Salih Fendoglu & Burak Saltoglu, 2009. "MIDAS Volatility Forecast Performance Under Market Stress: Evidence from Emerging and Developed Stock Markets," Working Papers 2009/04, Bogazici University, Department of Economics.
    29. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    30. Cláudia Duarte, 2015. "Covariate-augmented unit root tests with mixed-frequency data," Working Papers w201507, Banco de Portugal, Economics and Research Department.
    31. González-Sánchez, Mariano & Nave, Juan & Rubio, Gonzalo, 2020. "Effects of uncertainty and risk aversion on the exposure of investment-style factor returns to real activity," Research in International Business and Finance, Elsevier, vol. 53(C).
    32. 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.
    33. Bräuning, Falk & Koopman, Siem Jan, 2014. "Forecasting macroeconomic variables using collapsed dynamic factor analysis," International Journal of Forecasting, Elsevier, vol. 30(3), pages 572-584.
    34. Nikolaus Hautsch & Fuyu Yang, 2014. "Bayesian Stochastic Search for the Best Predictors: Nowcasting GDP Growth," University of East Anglia Applied and Financial Economics Working Paper Series 056, School of Economics, University of East Anglia, Norwich, UK..
    35. Layna Mosley & Victoria Paniagua & Erik Wibbels, 2020. "Moving markets? Government bond investors and microeconomic policy changes," Economics and Politics, Wiley Blackwell, vol. 32(2), pages 197-249, July.
    36. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    37. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    38. Qifa Xu & Lu Chen & Cuixia Jiang & Yezheng Liu, 2022. "Forecasting expected shortfall and value at risk with a joint elicitable mixed data sampling model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 407-421, April.
    39. Chang, Tsangyao & Hsu, Chen-Min & Chen, Sheng-Tung & Wang, Mei-Chih & Wu, Cheng-Feng, 2023. "Revisiting economic growth and CO2 emissions nexus in Taiwan using a mixed-frequency VAR model," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 319-342.
    40. Anthony S. Tay, 2006. "Mixing Frequencies : Stock Returns as a Predictor of Real Output Growth," Macroeconomics Working Papers 22480, East Asian Bureau of Economic Research.
    41. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    42. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    43. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2020. "Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality," Journal of Econometrics, Elsevier, vol. 218(2), pages 633-654.
    44. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    45. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    46. Shuichi Nagata, 2012. "Consistent Estimation of Integrated Volatility Using Intraday Absolute Returns for SV Jump Diffusion Processes," Economics Bulletin, AccessEcon, vol. 32(1), pages 306-314.
    47. Becker, Ralf & Clements, Adam E. & White, Scott I., 2007. "Does implied volatility provide any information beyond that captured in model-based volatility forecasts?," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2535-2549, August.
    48. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    49. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    50. Qian Chen & Xiang Gao & Shan Xie & Li Sun & Shuairu Tian & Shigeyuki Hamori, 2021. "On the Predictability of China Macro Indicator with Carbon Emissions Trading," Energies, MDPI, vol. 14(5), pages 1-24, February.
    51. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    52. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    53. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    54. Valadkhani, Abbas & Smyth, Russell, 2017. "How do daily changes in oil prices affect US monthly industrial output?," Energy Economics, Elsevier, vol. 67(C), pages 83-90.
    55. Sarun Kamolthip, 2021. "Macroeconomic forecasting with LSTM and mixed frequency time series data," Papers 2109.13777, arXiv.org.
    56. Hideyuki Takamizawa, 2015. "Predicting Interest Rate Volatility Using Information on the Yield Curve," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 347-386, September.
    57. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    58. Ryan T. Ball & Lindsey Gallo & Eric Ghysels, 2019. "Tilting the evidence: the role of firm-level earnings attributes in the relation between aggregated earnings and gross domestic product," Review of Accounting Studies, Springer, vol. 24(2), pages 570-592, June.
    59. Marín Díazaraque, Juan Miguel & Rue, Havard & Lopes Moreira Da Veiga, María Helena & Zea Bermudez, Patrícia de, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de Estadística.
    60. Henryk Gurgul & Roland Mestel & Robert Syrek, 2017. "MIDAS models in banking sector – systemic risk comparison," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 18(2), pages 165-181.
    61. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    62. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.
    63. Cheng, Ai-Ru & Jahan-Parvar, Mohammad R., 2014. "Risk–return trade-off in the pacific basin equity markets," Emerging Markets Review, Elsevier, vol. 18(C), pages 123-140.
    64. Sarah Goldman & Virginia Zhelyazkova, 2023. "CO2 Emissions and GDP: A Revisited Kuznets Curve Version via a Panel Threshold MIDAS-VAR Model in Europe for a Recent Period," Economic Research Guardian, Weissberg Publishing, vol. 13(2), pages 82-99, December.
    65. Stankevich, Ivan, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
    66. Ana Beatriz Galvão & Michael Owyang, 2022. "Forecasting low‐frequency macroeconomic events with high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1314-1333, November.
    67. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    68. Emre Alper, C. & Fendoglu, Salih & Saltoglu, Burak, 2012. "MIDAS volatility forecast performance under market stress: Evidence from emerging stock markets," Economics Letters, Elsevier, vol. 117(2), pages 528-532.
    69. Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2008. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," BIS Working Papers 249, Bank for International Settlements.
    70. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    71. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
    72. Ghysels, Eric & Sinko, Arthur, 2011. "Volatility forecasting and microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 257-271, January.
    73. Claudia FORONI & Massimiliano MARCELLINO, 2012. "A Comparison of Mixed Frequency Approaches for Modelling Euro Area Macroeconomic Variables," Economics Working Papers ECO2012/07, European University Institute.
    74. Fulvio Corsi & Davide Pirino & Roberto Renò, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Post-Print hal-00741630, HAL.
    75. John M Maheu & Thomas H McCurdy, 2008. "Do high-frequency measures of volatility improve forecasts of return distributions?," Working Papers tecipa-324, University of Toronto, Department of Economics.
    76. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    77. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    78. Michael P. Clements & Ana Beatriz Galvão, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206, November.
    79. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    80. Andrew J. Patton & Tarun Ramadorai, 2013. "On the High-Frequency Dynamics of Hedge Fund Risk Exposures," Journal of Finance, American Finance Association, vol. 68(2), pages 597-635, April.
    81. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    82. Bai, Yiyi & Okullo, Samuel J., 2023. "Drivers and pass-through of the EU ETS price: Evidence from the power sector," Energy Economics, Elsevier, vol. 123(C).
    83. Wing Hong Chan & Ranjini Jha & Madhu Kalimipalli, 2009. "The Economic Value Of Using Realized Volatility In Forecasting Future Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 231-259, September.
    84. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    85. El-Shagi, Makram, 2016. "Much ado about nothing: Sovereign ratings and government bond yields in the OECD," IWH Discussion Papers 22/2016, Halle Institute for Economic Research (IWH).
    86. Ekaterina Smetanina, 2017. "Real-Time GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 561-601.
    87. Jad Beyhum & Jonas Striaukas, 2023. "Sparse plus dense MIDAS regressions and nowcasting during the COVID pandemic," Papers 2306.13362, arXiv.org, revised Dec 2023.
    88. Guillaume Bagnarosa & Mark Cummins & Michael Dowling & Fearghal Kearney, 2022. "Commodity risk in European dairy firms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 151-181.
    89. Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    90. 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.
    91. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    92. Hwang, Eunju & Shin, Dong Wan, 2014. "Infinite-order, long-memory heterogeneous autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 339-358.
    93. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    94. Ghysels, Eric & Guérin, Pierre & Marcellino, Massimiliano, 2014. "Regime switches in the risk–return trade-off," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 118-138.
    95. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    96. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    97. Gopal K. Basak & Ravi Jagannathan & Tongshu Ma, 2004. "A Jackknife Estimator for Tracking Error Variance of Optimal Portfolios Constructed Using Estimated Inputs1," NBER Working Papers 10447, National Bureau of Economic Research, Inc.
    98. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    99. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    100. Nystrup, Peter & Lindström, Erik & Møller, Jan K. & Madsen, Henrik, 2021. "Dimensionality reduction in forecasting with temporal hierarchies," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1127-1146.
    101. Kambouroudis, Dimos S. & McMillan, David G., 2015. "Is there an ideal in-sample length for forecasting volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 114-137.
    102. Ioannis Chalkiadakis & Gareth W. Peters & Matthew Ames, 2023. "Hybrid ARDL-MIDAS-Transformer time-series regressions for multi-topic crypto market sentiment driven by price and technology factors," Digital Finance, Springer, vol. 5(2), pages 295-365, June.
    103. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," Discussion Paper Series 1: Economic Studies 2011,35, Deutsche Bundesbank.
    104. Philip Hans Franses, 2019. "On inflation expectations in the NKPC model," Empirical Economics, Springer, vol. 57(6), pages 1853-1864, December.
    105. Marcos Bujosa & Antonio García‐Ferrer & Aránzazu de Juan & Antonio Martín‐Arroyo, 2020. "Evaluating early warning and coincident indicators of business cycles using smooth trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 1-17, January.
    106. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    107. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
    108. Andreou, Elena & Ghysels, Eric, 2006. "Monitoring disruptions in financial markets," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 77-124.
    109. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    110. Stefano Grassi & Nima Nonejad & Paolo Santucci de Magistris, 2014. "Forecasting with the Standardized Self-Perturbed Kalman Filter," CREATES Research Papers 2014-12, Department of Economics and Business Economics, Aarhus University.
    111. Mei, Dexiang & Zhao, Chenchen & Luo, Qin & Li, Yan, 2022. "Forecasting the Chinese low-carbon index volatility," Resources Policy, Elsevier, vol. 77(C).
    112. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    113. 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).
    114. 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.
    115. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
    116. Maojun Zhang & Yang Zhao & Jiangxia Nan, 2022. "Economic policy uncertainty and volatility of treasury futures," Review of Derivatives Research, Springer, vol. 25(1), pages 93-107, April.
    117. León Valle Ángel & Nave Pineda Juan & Rubio Irigoyen Gonzalo, 2005. "The Relationship between Risk and Expected Return in Europe," Working Papers 201025, Fundacion BBVA / BBVA Foundation.
    118. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
    119. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    120. 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.
    121. H. J. Turtle & Kainan Wang, 2014. "Modeling Conditional Covariances With Economic Information Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 217-236, April.
    122. Fang, Libing & Yu, Honghai & Xiao, Wen, 2018. "Forecasting gold futures market volatility using macroeconomic variables in the United States," Economic Modelling, Elsevier, vol. 72(C), pages 249-259.
    123. Salisu, Afees A. & Ogbonna, Ahamuefula E., 2019. "Another look at the energy-growth nexus: New insights from MIDAS regressions," Energy, Elsevier, vol. 174(C), pages 69-84.
    124. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    125. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    126. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2015. "Fundamentals and the Volatility of Real Estate Prices in China: A Sequential Modelling Strategy," Working Papers 222015, Hong Kong Institute for Monetary Research.
    127. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    128. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    129. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    130. Liu, Xinyi & Margaritis, Dimitris & Wang, Peiming, 2012. "Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 483-496.
    131. Valadkhani, Abbas & Smyth, Russell, 2018. "Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes," Energy Economics, Elsevier, vol. 69(C), pages 89-100.
    132. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    133. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    134. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.
    135. Visser, Marcel P., 2008. "Garch Parameter Estimation Using High-Frequency Data," MPRA Paper 9076, University Library of Munich, Germany.
    136. Ooft, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    137. Wong, Wing-Keung & McAleer, Michael, 2009. "Mapping the Presidential Election Cycle in US stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(11), pages 3267-3277.
    138. 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).
    139. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A. & Ferreira, Paulo & Aslam, Faheem & Tabak, Benjamin Miranda, 2022. "Interplay multifractal dynamics among metal commodities and US-EPU," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    140. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    141. Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    142. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    143. Anindya Biswas, 2015. "The output gap and inflation in U.S. data: an empirical note," Economics Bulletin, AccessEcon, vol. 35(2), pages 841-845.
    144. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    145. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    146. Huiling Yuan & Yong Zhou & Zhiyuan Zhang & Xiangyu Cui, 2019. "Forecasting security's volatility using low-frequency historical data, high-frequency historical data and option-implied volatility," Papers 1907.02666, arXiv.org.
    147. Talavera, Oleksandr & Tsapin, Andriy & Zholud, Oleksandr, 2012. "Macroeconomic uncertainty and bank lending: The case of Ukraine," Economic Systems, Elsevier, vol. 36(2), pages 279-293.
    148. Seo, Sung Won & Kim, Jun Sik, 2015. "The information content of option-implied information for volatility forecasting with investor sentiment," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 106-120.
    149. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    150. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    151. Huiling Yuan & Guodong Li & Junhui Wang, 2022. "High-Frequency-Based Volatility Model with Network Structure," Papers 2204.12933, arXiv.org.
    152. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    153. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    154. 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).
    155. Bandi, Federico M. & Russell, Jeffrey R., 2011. "Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations," Journal of Econometrics, Elsevier, vol. 160(1), pages 145-159, January.
    156. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    157. Santiago Etchegaray Alvarez, 2022. "Proyecciones macroeconómicas con datos en frecuencias mixtas. Modelos ADL-MIDAS, U-MIDAS y TF-MIDAS con aplicaciones para Uruguay," Documentos de trabajo 2022004, Banco Central del Uruguay.
    158. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    159. Emiliano Magrini & Ayca Donmez, 2013. "Agricultural Commodity Price Volatility and Its Macroeconomic Determinants: A GARCH-MIDAS Approach," JRC Research Reports JRC84138, Joint Research Centre.
    160. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models: from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
    161. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    162. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    163. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
    164. Qifa Xu & Zezhou Wang & Cuixia Jiang & Yezheng Liu, 2023. "Deep learning on mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2099-2120, December.
    165. Biswas, Anindya, 2014. "The output gap and expected security returns," Review of Financial Economics, Elsevier, vol. 23(3), pages 131-140.
    166. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
    167. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    168. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
    169. Eric Girardin & Roselyne Joyeux, 2013. "Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach," Post-Print hal-01499615, HAL.
    170. Alexander Correa, 2021. "Forecasting Tourist Arrivals to Colombia from Google Trends Search Criteria," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 95, pages 105-134, July-Dece.
    171. 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.
    172. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    173. Elena Andreou & Andros Kourtellos, 2015. "The State and the Future of Cyprus Macroeconomic Forecasting," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 9(1), pages 73-90, June.
    174. Fady Barsoum & Sandra Stankiewicz, 2013. "Forecasting GDP Growth Using Mixed-Frequency Models With Switching Regimes," Working Paper Series of the Department of Economics, University of Konstanz 2013-10, Department of Economics, University of Konstanz.
    175. Jong-Min Kim & Hojin Jung & Li Qin, 2017. "A new generalized volatility proxy via the stochastic volatility model," Applied Economics, Taylor & Francis Journals, vol. 49(23), pages 2259-2268, May.
    176. Ioannis Kasparis & Peter C.B. Phillips, 2009. "Dynamic Misspecification in Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 1700, Cowles Foundation for Research in Economics, Yale University.
    177. Alexander Aue & Lajos Horváth & Clifford M. Hurvich & Philippe Soulier, 2014. "Limit Laws in Transaction-Level Asset Price Models," Post-Print hal-00583372, HAL.
    178. Chen, Wang & Lu, Xinjie & Wang, Jiqian, 2022. "Modeling and managing stock market volatility using MRS-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 625-635.
    179. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    180. Kunst, Robert M. & Franses, Philip Hans, 2010. "Asymmetric Time Aggregation and its Potential Benefits for Forecasting Annual Data," Economics Series 252, Institute for Advanced Studies.
    181. Lee A. Smales, 2021. "The effect of treasury auctions on 10‐year Treasury note futures," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 1517-1555, April.
    182. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    183. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    184. 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.
    185. Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
    186. Benoît Sévi, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Post-Print hal-01500860, HAL.
    187. Lucian-Liviu Albu & Radu Lupu & Adrian Cantemir Calin, 2015. "Interactions between financial markets and macroeconomic variables in EU: a nonlinear modeling approach," ERSA conference papers ersa15p685, European Regional Science Association.
    188. Ghysels, Eric & Ball, Ryan, 2017. "Automated Earnings Forecasts:- Beat Analysts or Combine and Conquer?," CEPR Discussion Papers 12179, C.E.P.R. Discussion Papers.
    189. MAMATZAKIS, emmanuel & MAMATZAKIS, E, 2022. "Understanding the impact of travel on wellbeing: evidence for Great Britain during the pandemic," MPRA Paper 112974, University Library of Munich, Germany.
    190. Lynda Khalaf & Maral Kichian & Charles Saunders & Marcel Voia, 2021. "Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit," Post-Print hal-03528880, HAL.
    191. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
    192. Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and Application," Papers 2008.03600, arXiv.org, revised Nov 2021.
    193. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    194. Adam Clements & Annastiina Silvennoinen, 2009. "On the economic benefit of utility based estimation of a volatility model," NCER Working Paper Series 44, National Centre for Econometric Research.
    195. Clements, Michael P. & Galvao, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation," Economic Research Papers 269743, University of Warwick - Department of Economics.
    196. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    197. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    198. Pradeep Mishra & Khder Alakkari & Mostafa Abotaleb & Pankaj Kumar Singh & Shilpi Singh & Monika Ray & Soumitra Sankar Das & Umme Habibah Rahman & Ali J. Othman & Nazirya Alexandrovna Ibragimova & Gulf, 2021. "Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)," Data, MDPI, vol. 6(11), pages 1-15, November.
    199. Ghysels, Eric & Sohn, Bumjean, 2009. "Which power variation predicts volatility well?," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 686-700, September.
    200. Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018. "Mixed frequency models with MA components," Discussion Papers 02/2018, Deutsche Bundesbank.
    201. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Cholesky-MIDAS model for predicting stock portfolio volatility," Centre for Growth and Business Cycle Research Discussion Paper Series 149, Economics, The University of Manchester.
    202. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2019. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Papers 1912.06307, arXiv.org, revised Feb 2021.
    203. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2015. "Testing for Granger causality in large mixed-frequency VARs," Discussion Papers 45/2015, Deutsche Bundesbank.
    204. He, Yongda & Lin, Boqiang, 2018. "Forecasting China's total energy demand and its structure using ADL-MIDAS model," Energy, Elsevier, vol. 151(C), pages 420-429.
    205. Viceira, Luis M., 2012. "Bond risk, bond return volatility, and the term structure of interest rates," International Journal of Forecasting, Elsevier, vol. 28(1), pages 97-117.
    206. Marcin Kacperczyk & Paul Damien & Stephen G. Walker, 2013. "A new class of Bayesian semi-parametric models with applications to option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 967-980, May.
    207. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    208. Jianhao Lin & Jiacheng Fan & Yifan Zhang & Liangyuan Chen, 2023. "Real‐time macroeconomic projection using narrative central bank communication," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 202-221, March.
    209. Kerssenfischer, Mark & Schmeling, Maik, 2022. "What moves markets?," Discussion Papers 16/2022, Deutsche Bundesbank.
    210. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    211. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    212. Afees A. Salisu & Raymond Swaray, 2020. "Forecasting the Return Volatility of Energy Prices: A GARCH-MIDAS Approach," World Scientific Book Chapters, in: Stéphane Goutte & Duc Khuong Nguyen (ed.), HANDBOOK OF ENERGY FINANCE Theories, Practices and Simulations, chapter 3, pages 47-71, World Scientific Publishing Co. Pte. Ltd..
    213. Belén Nieto & Alfonso Novales Cinca & Gonzalo Rubio, 2014. "Macroeconomic and Financial Determinants of the Volatility of Corporate Bond Returns," Documentos de Trabajo del ICAE 2014-25, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    214. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
    215. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    216. Smales, L.A., 2021. "Macroeconomic news and treasury futures return volatility: Do treasury auctions matter?," Global Finance Journal, Elsevier, vol. 48(C).
    217. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    218. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    219. Ralf Becker & Denise R. Osborn, 2012. "Weighted Smooth Transition Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 795-811, August.
    220. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    221. Rong Fu & Luze Xie & Tao Liu & Juan Huang & Binbin Zheng, 2022. "Chinese Economic Growth Projections Based on Mixed Data of Carbon Emissions under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    222. Qian, Hang, 2010. "Vector autoregression with varied frequency data," MPRA Paper 34682, University Library of Munich, Germany.
    223. Qian, Hang, 2016. "A computationally efficient method for vector autoregression with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 433-437.
    224. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    225. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
    226. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Post-Print halshs-04344131, HAL.
    227. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    228. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    229. Wink Junior, Marcos Vinício & Pereira, Pedro Luiz Valls, 2011. "Modeling and Forecasting of Realized Volatility: Evidence from Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(2), December.
    230. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    231. Nobuyuki Hanaki & Cars Hommes & Dávid Kopányi & Anita Kopányi-Peuker & Jan Tuinstra, 2023. "Forecasting returns instead of prices exacerbates financial bubbles," Experimental Economics, Springer;Economic Science Association, vol. 26(5), pages 1185-1213, November.
    232. Diego J. Pedregal & Javier J. Pérez & Antonio Sánchez Fuentes, 2014. "A Tookit to strengthen Government," Hacienda Pública Española / Review of Public Economics, IEF, vol. 211(4), pages 117-146, December.
    233. Wang, Zijun & Khan, M. Moosa, 2017. "Market states and the risk-return tradeoff," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 314-327.
    234. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yu, Keming, 2020. "Mixed data sampling expectile regression with applications to measuring financial risk," Economic Modelling, Elsevier, vol. 91(C), pages 469-486.
    235. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    236. Teresa Leal & Diego Pedregal & Javier Pérez, 2011. "Short-term monitoring of the Spanish government balance," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 2(1), pages 97-119, March.
    237. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je & Gau, Yin-Feng, 2022. "Risk-return trade-off in the Australian Securities Exchange: Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 384-401.
    238. Afees A. Salisu & Rangan Gupta, 2019. "How do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Working Papers 201946, University of Pretoria, Department of Economics.
    239. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    240. Boyao Wu & Difang Huang & Muzi Chen, 2024. "Estimating Contagion Mechanism in Global Equity Market with Time-Zone Effect," Papers 2404.04335, arXiv.org.
    241. Libing Fang & Baizhu Chen & Honghai Yu & Yichuo Qian, 2018. "The importance of global economic policy uncertainty in predicting gold futures market volatility: A GARCH‐MIDAS approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 413-422, March.
    242. Hale, Galina & Lopez, Jose A., 2019. "Monitoring banking system connectedness with big data," Journal of Econometrics, Elsevier, vol. 212(1), pages 203-220.
    243. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
    244. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    245. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    246. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    247. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    248. Adediran, Idris A. & Swaray, Raymond, 2023. "Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty," Economic Modelling, Elsevier, vol. 123(C).
    249. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Forecasting," Papers 2404.02671, arXiv.org.
    250. 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.
    251. Yimin Yang & Fei Jia & Haoran Li, 2023. "Estimation of Panel Data Models with Mixed Sampling Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 514-544, June.
    252. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    253. 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.
    254. Joe Hirschberg & Jenny Lye, 2021. "Estimating risk premiums for regulated firms when accounting for reference-day variation and high-order moments of return volatility," Environment Systems and Decisions, Springer, vol. 41(3), pages 455-467, September.
    255. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    256. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    257. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    258. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    259. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
    260. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    261. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
    262. Wang, Tianyi & Liang, Fang & Huang, Zhuo & Yan, Hong, 2022. "Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model," Economic Modelling, Elsevier, vol. 109(C).
    263. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    264. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla & Masih, A. Mansur M., 2014. "Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model," MPRA Paper 56965, University Library of Munich, Germany.
    265. J. Isaac Miller & Xi Wang, 2016. "Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 810-824, November.
    266. Halbleib, Roxana & Dimitriadis, Timo, 2019. "How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203669, Verein für Socialpolitik / German Economic Association.
    267. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    268. 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.
    269. Amir Safari & Detlef Seese, 2010. "Behavior of realized volatility and correlation in exchange markets," International Econometric Review (IER), Econometric Research Association, vol. 2(2), pages 73-96, September.
    270. Michael P. Clements & Ana Beatriz Galvão, 2014. "Measuring Macroeconomic Uncertainty: US Inflation and Output Growth," ICMA Centre Discussion Papers in Finance icma-dp2014-04, Henley Business School, University of Reading.
    271. Proelss, Juliane & Schweizer, Denis & Seiler, Volker, 2020. "The economic importance of rare earth elements volatility forecasts," International Review of Financial Analysis, Elsevier, vol. 71(C).
    272. 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.
    273. Ralf Becker & Adam Clements, 2007. "Forecasting stock market volatility conditional on macroeconomic conditions," NCER Working Paper Series 18, National Centre for Econometric Research.
    274. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    275. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    276. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    277. Wenting Liu & Zhaozhong Gui & Guilin Jiang & Lihua Tang & Lichun Zhou & Wan Leng & Xulong Zhang & Yujiang Liu, 2023. "Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data," Papers 2309.16196, arXiv.org.
    278. Henker, Thomas & Husodo, Zaäfri A., 2010. "Noise and efficient variance in the Indonesia Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 199-216, April.
    279. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2013. "On the Benefits of Equicorrelation for Portfolio Allocation," NCER Working Paper Series 99, National Centre for Econometric Research.
    280. Pérez, Javier J. & Pedregal, Diego J., 2008. "Should quarterly government finance statistics be used for fiscal surveillane in Europe?," Working Paper Series 937, European Central Bank.
    281. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
    282. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    283. Qu, Hui & Chen, Wei & Niu, Mengyi & Li, Xindan, 2016. "Forecasting realized volatility in electricity markets using logistic smooth transition heterogeneous autoregressive models," Energy Economics, Elsevier, vol. 54(C), pages 68-76.
    284. Huang, Xiaozhou & Wang, Yubao & Song, Juan, 2023. "The Chinese oil futures volatility: Evidence from high-low estimator information," Finance Research Letters, Elsevier, vol. 56(C).
    285. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
    286. Murat Körs & Mehmet Baha Karan, 2023. "Stock exchange volatility forecasting under market stress with MIDAS regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 295-306, January.
    287. Bonino-Gayoso, Nicolás & García-Hiernaux, Alfredo, 2019. "TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables," MPRA Paper 93366, University Library of Munich, Germany.
    288. Bandi, Federico M. & Russell, Jeffrey R. & Yang, Chen, 2008. "Realized volatility forecasting and option pricing," Journal of Econometrics, Elsevier, vol. 147(1), pages 34-46, November.
    289. Cláudia Duarte, 2014. "Autoregressive augmentation of MIDAS regressions," Working Papers w201401, Banco de Portugal, Economics and Research Department.
    290. Eric Ghysels & Alberto Plazzi & Rossen Valkanov, 2007. "Valuation in US Commercial Real Estate," European Financial Management, European Financial Management Association, vol. 13(3), pages 472-497, June.
    291. Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
    292. Baur, Dirk G. & Dimpfl, Thomas, 2016. "Googling gold and mining bad news," Resources Policy, Elsevier, vol. 50(C), pages 306-311.
    293. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    294. Anthony S. Tay, 2007. "Financial Variables as Predictors of Real Output Growth," Development Economics Working Papers 22482, East Asian Bureau of Economic Research.
    295. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    296. Bhanu Pratap & Nalin Priyaranjan, 2023. "Macroeconomic effects of uncertainty: a Google trends-based analysis for India," Empirical Economics, Springer, vol. 65(4), pages 1599-1625, October.
    297. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
    298. Manabu Asai, 2013. "Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 469-480, August.
    299. Alejandro Fernández Cerezo, 2023. "A supply-side GDP nowcasting model," Economic Bulletin, Banco de España, issue 2023/Q1.
    300. Khoo, Joye & Cheung, Adrian (Wai Kong), 2021. "Does geopolitical uncertainty affect corporate financing? Evidence from MIDAS regression," Global Finance Journal, Elsevier, vol. 47(C).
    301. Alper, C. Emre & Fendoglu, Salih & Saltoglu, Burak, 2008. "Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets," MPRA Paper 7460, University Library of Munich, Germany.
    302. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
    303. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
    304. Leon, Angel & Nave, Juan M. & Rubio, Gonzalo, 2007. "The relationship between risk and expected return in Europe," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 495-512, February.
    305. Clements, Michael P. & Galvão, Ana Beatriz, 2017. "Model and survey estimates of the term structure of US macroeconomic uncertainty," International Journal of Forecasting, Elsevier, vol. 33(3), pages 591-604.
    306. Anderson, Evan W. & Ghysels, Eric & Juergens, Jennifer L., 2009. "The impact of risk and uncertainty on expected returns," Journal of Financial Economics, Elsevier, vol. 94(2), pages 233-263, November.
    307. Pacifico, Antonio, 2020. "Bayesian Fuzzy Clustering with Robust Weighted Distance for Multiple ARIMA and Multivariate Time-Series," MPRA Paper 104379, University Library of Munich, Germany.
    308. Baele, Lieven & Londono, Juan M., 2013. "Understanding industry betas," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 30-51.
    309. Robin de Vilder & Marcel P. Visser, 2007. "Proxies for daily volatility," PSE Working Papers halshs-00588307, HAL.
    310. Aharon, David Y. & Qadan, Mahmoud, 2018. "What drives the demand for information in the commodity market?," Resources Policy, Elsevier, vol. 59(C), pages 532-543.
    311. Damien Kunjal & Faeezah Peerbhai & Paul-Francois Muzindutsi, 2022. "Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach," Risk Management, Palgrave Macmillan, vol. 24(3), pages 236-258, September.
    312. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    313. J. Isaac Miller, 2014. "Simple Robust Tests for the Specification of High-Frequency Predictors of a Low-Frequency Series," Working Papers 1412, Department of Economics, University of Missouri.
    314. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    315. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    316. Christoffersen, Peter & Mazzotta, Stefano, 2004. "The informational content of over-the-counter currency options," Working Paper Series 366, European Central Bank.
    317. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    318. Belcaid, Karim & El Ghini, Ahmed, 2019. "U.S., European, Chinese economic policy uncertainty and Moroccan stock market volatility," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    319. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
    320. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.
    321. Clements, A. & Silvennoinen, A., 2013. "Volatility timing: How best to forecast portfolio exposures," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 108-115.
    322. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    323. Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
    324. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
    325. Keiichi Goshima & Hiroshi Ishijima & Mototsugu Shintani & Hiroki Yamamoto, 2019. "Forecasting Japanese inflation with a news-based leading indicator of economic activities," CARF F-Series CARF-F-458, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    326. Virmantas Kvedaras & Alfredas Račkauskas, 2010. "Regression Models with Variables of Different Frequencies: The Case of a Fixed Frequency Ratio," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 600-620, October.
    327. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    328. Tseng Tseng-Chan & Chung Huimin & Huang Chin-Sheng, 2009. "Modeling Jump and Continuous Components in the Volatility of Oil Futures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-30, May.
    329. Ojogho, Osaihiomwan & Egware, Robert Awotu, 2015. "Price Generating Process And Volatility In Nigerian Agricultural Commodities Market," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(4), pages 1-10, October.
    330. Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
    331. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    332. 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.
    333. Bangwayo-Skeete, Prosper F. & Skeete, Ryan W., 2015. "Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach," Tourism Management, Elsevier, vol. 46(C), pages 454-464.
    334. Gong, Xu & Sun, Yi & Du, Zhili, 2022. "Geopolitical risk and China's oil security," Energy Policy, Elsevier, vol. 163(C).
    335. Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 521-536.
    336. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    337. 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.
    338. Dimitra Lamprou, 2015. "Nowcasting GDP in Greece: A Note on Forecasting Improvements from the Use of Bridge Models," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(1), pages 85-100.
    339. Ryan T. Ball & Eric Ghysels, 2018. "Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?," Management Science, INFORMS, vol. 64(10), pages 4936-4952, October.
    340. Rodriguez, Abel & Puggioni, Gavino, 2010. "Mixed frequency models: Bayesian approaches to estimation and prediction," International Journal of Forecasting, Elsevier, vol. 26(2), pages 293-311, April.
    341. Chan-Guk Huh & Jie Wu, 2015. "Linkage between US monetary policy and emerging economies: the case of Korea?s financial market and monetary policy," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 4(3), pages 1-18, September.
    342. Wang, Jianxin & Yang, Minxian, 2009. "Asymmetric volatility in the foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 597-615, October.
    343. Yang, Cheng-Hu & Wang, Hai-Tang & Ma, Xin & Talluri, Srinivas, 2023. "A data-driven newsvendor problem: A high-dimensional and mixed-frequency method," International Journal of Production Economics, Elsevier, vol. 266(C).
    344. Sara Boni & Massimiliano Caporin & Francesco Ravazzolo, 2024. "Nowcasting Inflation at Quantiles: Causality from Commodities," BEMPS - Bozen Economics & Management Paper Series BEMPS102, Faculty of Economics and Management at the Free University of Bozen.
    345. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    346. Zhang, Ning & Su, Xiaoman & Qi, Shuyuan, 2023. "An empirical investigation of multiperiod tail risk forecasting models," International Review of Financial Analysis, Elsevier, vol. 86(C).
    347. Łukasz Lenart & Agnieszka Leszczyńska-Paczesna, 2016. "Do market prices improve the accuracy of inflation forecasting in Poland? A disaggregated approach," Bank i Kredyt, Narodowy Bank Polski, vol. 47(5), pages 365-394.
    348. Eunjeong Choi & Soohwan Cho & Dong Keun Kim, 2020. "Power Demand Forecasting using Long Short-Term Memory (LSTM) Deep-Learning Model for Monitoring Energy Sustainability," Sustainability, MDPI, vol. 12(3), pages 1-14, February.
    349. Emmanuel Mamatzakis & Mike G. Tsionas & Steven Ongena, 2023. "Why do households repay their debt in UK during the COVID-19 crisis?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(8), pages 1789-1823, April.
    350. Andrianady, Josué R. & Rajaonarison, Njakanasandratra R. & Razanajatovo, Yves H., 2023. "Estimating Madagascar economic growth using the Mixed Data Sampling (MIDAS) approach," MPRA Paper 118267, University Library of Munich, Germany.
    351. 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).
    352. Neville Francis & Eric Ghysels & Michael T. Owyang, 2011. "The low-frequency impact of daily monetary policy shocks," Working Papers 2011-009, Federal Reserve Bank of St. Louis.
    353. Jian Zhou, 2017. "Forecasting REIT volatility with high-frequency data: a comparison of alternative methods," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2590-2605, June.
    354. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    355. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    356. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
    357. Motegi, Kaiji & Sadahiro, Akira, 2018. "Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 118-128.
    358. Ryan T. Ball, 2013. "Does Anticipated Information Impose a Cost on Risk‐Averse Investors? A Test of the Hirshleifer Effect," Journal of Accounting Research, Wiley Blackwell, vol. 51(1), pages 31-66, March.
    359. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    360. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
    361. Nava, Consuelo R. & Osti, Linda & Zoia, Maria Grazia, 2022. "Forecasting Domestic Tourism across Regional Destinations through MIDAS Regressions," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202207, University of Turin.
    362. Neville Francis, 2012. "The Low-Frequency Impact of Daily Monetary Policy Shock," 2012 Meeting Papers 198, Society for Economic Dynamics.
    363. Tumala, Mohammed M. & Salisu, Afees A. & Atoi, Ngozi V., 2022. "Oil-growth nexus in Nigeria: An ADL-MIDAS approach," Resources Policy, Elsevier, vol. 77(C).
    364. Francisco Blasques & Siem Jan Koopman & Max Mallee, 2014. "Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-105/III, Tinbergen Institute.
    365. Visser, Marcel P., 2008. "Forecasting S&P 500 Daily Volatility using a Proxy for Downward Price Pressure," MPRA Paper 11100, University Library of Munich, Germany.
    366. Huang, Lin & Wang, Zijun, 2014. "Is the investment factor a proxy for time-varying investment opportunities? The US and international evidence," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 219-232.
    367. Anders B. Trolle & Eduardo S. Schwartz, 2010. "An Empirical Analysis of the Swaption Cube," NBER Working Papers 16549, National Bureau of Economic Research, Inc.
    368. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
    369. Adlai Fisher & Charles Martineau & Jinfei Sheng, 2022. "Macroeconomic Attention and Announcement Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 35(11), pages 5057-5093.
    370. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    371. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    372. Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.
    373. Matěj Liberda, 2017. "Mixed-frequency Drivers of Precious Metal Prices," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(6), pages 2007-2015.
    374. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
    375. Maghyereh Aktham & Sweidan Osama & Awartani Basel, 2020. "Asymmetric Responses of Economic Growth to Daily Oil Price Changes: New Global Evidence from Mixed-data Sampling Approach," Review of Economics, De Gruyter, vol. 71(2), pages 81-99, August.
    376. Alberto Plazzi & Walter Torous & Rossen Valkanov, 2008. "The Cross‐Sectional Dispersion of Commercial Real Estate Returns and Rent Growth: Time Variation and Economic Fluctuations," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 36(3), pages 403-439, September.
    377. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    378. Lv, Wendai & Qi, Jipeng & Feng, Jing, 2023. "Economic policy uncertainty and environmental governance company volatility: Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
    379. Berger, Philip G., 2011. "Challenges and opportunities in disclosure research—A discussion of ‘the financial reporting environment: Review of the recent literature’," Journal of Accounting and Economics, Elsevier, vol. 51(1), pages 204-218.
    380. Laine, Olli-Matti & Lindblad, Annika, 2020. "Nowcasting Finnish GDP growth using financial variables: a MIDAS approach," BoF Economics Review 4/2020, Bank of Finland.
    381. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2011. "The Merit of High-Frequency Data in Portfolio Allocation," SFB 649 Discussion Papers SFB649DP2011-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    382. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.
    383. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
    384. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yuan, Jing, 2018. "Measuring systemic risk of the banking industry in China: A DCC-MIDAS-t approach," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 13-31.
    385. LUPU, Radu & CALIN, Adrian Cantemir, 2014. "A Mixed Frequency Analysis Of Connections Between Macroeconomic Variables And Stock Markets In Central And Eastern Europe," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 18(2), pages 69-79.
    386. Torun, Erdost & Chang, Tzu-Pu & Chou, Ray Y., 2020. "Causal relationship between spot and futures prices with multiple time horizons: A nonparametric wavelet Granger causality test," Research in International Business and Finance, Elsevier, vol. 52(C).
    387. Qian, Hang, 2010. "Linear regression using both temporally aggregated and temporally disaggregated data: Revisited," MPRA Paper 32686, University Library of Munich, Germany.
    388. Zhao, Ling, 2023. "Global economic policy uncertainty and oil futures volatility prediction," Finance Research Letters, Elsevier, vol. 54(C).
    389. Stefan Gebauer, 2017. "The Use of Financial Market Variables in Forecasting," DIW Roundup: Politik im Fokus 115, DIW Berlin, German Institute for Economic Research.
    390. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    391. Dimitrios Louzis & Spyros Xanthopoulos-Sisinis & Apostolos Refenes, 2011. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Post-Print hal-00709559, HAL.
    392. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
    393. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    394. Abdul-Aziz Ibn Musah & Jianguo Du & Hira Salah Ud din Khan & Alhassan Alolo Abdul-Rasheed Akeji, 2018. "The Asymptotic Decision Scenarios of an Emerging Stock Exchange Market: Extreme Value Theory and Artificial Neural Network," Risks, MDPI, vol. 6(4), pages 1-24, November.
    395. Dirk Drechsel & Stefan Neuwirth, 2016. "Taming volatile high frequency data with long lag structure: An optimal filtering approach for forecasting," KOF Working papers 16-407, KOF Swiss Economic Institute, ETH Zurich.
    396. Lee A. Smales, 2022. "The influence of policy uncertainty on exchange rate forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 997-1016, August.
    397. Shuting Liu & Qifa Xu & Cuixia Jiang, 2021. "Systemic risk of China’s commercial banks during financial turmoils in 2010-2020: A MIDAS-QR based CoVaR approach," Applied Economics Letters, Taylor & Francis Journals, vol. 28(18), pages 1600-1609, October.
    398. Adam Clements & Ralf Becker, 2009. "A nonparametric approach to forecasting realized volatility," NCER Working Paper Series 43, National Centre for Econometric Research.
    399. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
    400. George Filis & Stavros Degiannakis & Zacharias Bragoudakis, 2022. "Forecasting macroeconomic indicators for Eurozone and Greece: How useful are the oil price assumptions?," Working Papers 296, Bank of Greece.
    401. Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    402. Robert Akunga & Ahmad Hassan Ahmad & Simeon Coleman, 2023. "Financial market integration in sub‐Saharan Africa: How important is contagion?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3637-3653, October.
    403. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
    404. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
    405. Gomes, Pedro & Taamouti, Abderrahim, 2016. "In search of the determinants of European asset market comovements," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 103-117.
    406. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    407. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
    408. Selma Toker & Nimet Özbay & Kristofer Månsson, 2022. "Mixed data sampling regression: Parameter selection of smoothed least squares estimator," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 718-751, July.
    409. Holmberg, Johan, 2021. "Earnings and Employment Dynamics: Capturing Cyclicality using Mixed Frequency Data," Umeå Economic Studies 991, Umeå University, Department of Economics.

  7. Pedro Santa-Clara & Shu Yan, 2004. "Jump and Volatility Risk and Risk Premia: A New Model and Lessons from S&P 500 Options," NBER Working Papers 10912, National Bureau of Economic Research, Inc.

    Cited by:

    1. Santa-Clara, Pedro & Saretto, Alessio, 2004. "Option Strategies: Good Deals and Margin Calls," University of California at Los Angeles, Anderson Graduate School of Management qt0499w44p, Anderson Graduate School of Management, UCLA.
    2. León, Angel & Nave, Juan & Rubio Irigoyen, Gonzalo, 2005. "The Relationship between Risk and Expected Return in Europe," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    3. Boes, M.J., 2006. "Index options : Pricing, implied densities and returns," Other publications TiSEM e9ed8a9f-2472-430a-b666-9, Tilburg University, School of Economics and Management.
    4. Shuang Li & Yanli Zhou & Yonghong Wu & Xiangyu Ge, 2017. "Equilibrium approach of asset and option pricing under Lévy process and stochastic volatility," Australian Journal of Management, Australian School of Business, vol. 42(2), pages 276-295, May.
    5. Brennan, Michael J & LIU, XIAOQUAN & Xia, Yihong, 2005. "Option Pricing Kernels and the ICAPM," University of California at Los Angeles, Anderson Graduate School of Management qt4d90p8ss, Anderson Graduate School of Management, UCLA.
    6. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    7. Eva Ferreira & Mónica Gago & Angel León & Gonzalo Rubio, 2005. "An empirical comparison of the performance of alternative option pricing models," Investigaciones Economicas, Fundación SEPI, vol. 29(3), pages 483-523, September.
    8. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    9. Constantinides, George M. & Jackwerth, Jens Carsten & Perrakis, Stylianos, 2005. "Option pricing: Real and risk-neutral distributions," CoFE Discussion Papers 05/06, University of Konstanz, Center of Finance and Econometrics (CoFE).
    10. Rubio Irigoyen, Gonzalo & Ferreira García, María Eva & Gago, Mónica & León, Angel, 2002. "An empirical comparison of the performance of alternative option pricing models," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    11. George M. Constantinides & Jens Carsten Jackwerth & Stylianos Perrakis, 2008. "Mispricing of S&P 500 Index Options," NBER Working Papers 14544, National Bureau of Economic Research, Inc.
    12. Reinhold Hafner & Martin Wallmeier, 2007. "Volatility as an Asset Class: European Evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 13(7), pages 621-644.
    13. Marcos Escobar-Anel & Harold A. Moreno-Franco, 2019. "Dynamic portfolio strategies under a fully correlated jump-diffusion process," Annals of Finance, Springer, vol. 15(3), pages 421-453, September.

  8. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "There is a Risk-Return Tradeoff After All," CIRANO Working Papers 2004s-24, CIRANO.

    Cited by:

    1. Song, Zefang & Song, Xinyuan & Li, Yuan, 2023. "Bayesian Analysis of ARCH-M model with a dynamic latent variable," Econometrics and Statistics, Elsevier, vol. 28(C), pages 47-62.
    2. Antonia Lopez-Villavicencio & Valérie Mignon, 2016. "Exchange Rate Pass-through in Emerging Countries: Do the Inflation Environment, Monetary Policy Regime and Institutional Quality Matter?," Working Papers 2016-07, CEPII research center.
    3. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    4. Hui Guo & Robert F. Whitelaw, 2003. "Uncovering the Risk-Return Relation in the Stock Market," NBER Working Papers 9927, National Bureau of Economic Research, Inc.
    5. Escanciano, Juan Carlos & Pardo-Fernandez, Juan Carlos & Van Keilegom, Ingrid, 2013. "Semiparametric Estimation of Risk-return Relationships," LIDAM Discussion Papers ISBA 2013035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Wang, Wenzhao, 2020. "Institutional investor sentiment, beta, and stock returns," Finance Research Letters, Elsevier, vol. 37(C).
    7. Chotipong Charoensom, 2024. "An Estimation of Regime Switching Models with Nonlinear Endogenous Switching," PIER Discussion Papers 217, Puey Ungphakorn Institute for Economic Research.
    8. Cardak, Buly A. & Martin, Vance L., 2023. "Household willingness to take financial risk: Stockmarket movements and life‐cycle effects," Journal of Banking & Finance, Elsevier, vol. 149(C).
    9. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
    11. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in?finite order," CeMMAP working papers CWP53/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    13. Prabheesh, K.P. & Sasongko, Aryo & Indawan, Fiskara, 2023. "Did the policy responses influence credit and business cycle co-movement during the COVID-19 crisis? Evidence from Indonesia," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 243-255.
    14. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
    15. Marianne Andries & Valentin Haddad, 2017. "Information Aversion," NBER Working Papers 23958, National Bureau of Economic Research, Inc.
    16. Yao, Jing & Yang, Yiwen, 2023. "Risk-return tradeoff and serial correlation in the Chinese stock market: A bailout-driven crash feedback hypothesis," Economic Modelling, Elsevier, vol. 129(C).
    17. Pástor, Luboš & Sinha, Meenakshi & Swaminathan, Bhaskaran, 2006. "Estimating the Intertemporal Risk-Return Tradeoff Using the Implied Cost of Capital," CEPR Discussion Papers 5462, C.E.P.R. Discussion Papers.
    18. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    19. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    20. 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.
    21. Christensen, Bent Jesper & Dahl, Christian M. & Iglesias, Emma M., 2012. "Semiparametric inference in a GARCH-in-mean model," Journal of Econometrics, Elsevier, vol. 167(2), pages 458-472.
    22. C. Emre Alper & Salih Fendoglu & Burak Saltoglu, 2009. "MIDAS Volatility Forecast Performance Under Market Stress: Evidence from Emerging and Developed Stock Markets," Working Papers 2009/04, Bogazici University, Department of Economics.
    23. Li, Dandan & Ghoshray, Atanu & Morley, Bruce, 2012. "Measuring the risk premium in uncovered interest parity using the component GARCH-M model," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 167-176.
    24. Martin, Vance L. & Tang, Chrismin & Yao, Wenying, 2021. "Forecasting the volatility of asset returns: The informational gains from option prices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 862-880.
    25. Hong, Seok Young & Linton, Oliver, 2020. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Journal of Econometrics, Elsevier, vol. 219(2), pages 389-424.
    26. John Cotter & Enrique Salvador, 2014. "The non-linear trade-off between return and risk: a regime-switching multi-factor framework," Working Papers 201414, Geary Institute, University College Dublin.
    27. 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.
    28. González-Sánchez, Mariano & Nave, Juan & Rubio, Gonzalo, 2020. "Effects of uncertainty and risk aversion on the exposure of investment-style factor returns to real activity," Research in International Business and Finance, Elsevier, vol. 53(C).
    29. 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.
    30. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    31. Jin, Xiaoye, 2017. "Time-varying return-volatility relation in international stock markets," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 157-173.
    32. Chiang, Thomas C. & Chen, Xiaoyu, 2016. "Stock returns and economic fundamentals in an emerging market: An empirical investigation of domestic and global market forces," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 107-120.
    33. Antonio Díaz & Carlos Esparcia, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, CEPII research center, issue 166, pages 1-22.
    34. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2017. "Economic Policy Uncertainty and Long-Run Stock Market Volatility and Correlation," CREATES Research Papers 2018-12, Department of Economics and Business Economics, Aarhus University.
    35. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    36. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    37. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    38. Yuming Li, 2017. "Risks and rewards for momentum and reversal portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 289-315, August.
    39. Qian Chen & Xiang Gao & Shan Xie & Li Sun & Shuairu Tian & Shigeyuki Hamori, 2021. "On the Predictability of China Macro Indicator with Carbon Emissions Trading," Energies, MDPI, vol. 14(5), pages 1-24, February.
    40. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    41. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    42. Angelos Kanas, 2013. "The risk-return relation and VIX: evidence from the S&P 500," Empirical Economics, Springer, vol. 44(3), pages 1291-1314, June.
    43. Valadkhani, Abbas & Smyth, Russell, 2017. "How do daily changes in oil prices affect US monthly industrial output?," Energy Economics, Elsevier, vol. 67(C), pages 83-90.
    44. Marks, Joseph M. & Nam, Kiseok, 2018. "Intertemporal risk-return tradeoff in the short-run," Economics Letters, Elsevier, vol. 172(C), pages 81-84.
    45. Hui Guo & Robert Savickas, 2003. "Does idiosyncratic risk matter: another look," Working Papers 2003-025, Federal Reserve Bank of St. Louis.
    46. Sarun Kamolthip, 2021. "Macroeconomic forecasting with LSTM and mixed frequency time series data," Papers 2109.13777, arXiv.org.
    47. Hideyuki Takamizawa, 2015. "Predicting Interest Rate Volatility Using Information on the Yield Curve," International Review of Finance, International Review of Finance Ltd., vol. 15(3), pages 347-386, September.
    48. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    49. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2012. "On the Macroeconomic Determinants of the Long-Term Oil-Stock Correlation," Working Papers 0525, University of Heidelberg, Department of Economics.
    50. Cheng, Ai-Ru & Jahan-Parvar, Mohammad R., 2014. "Risk–return trade-off in the pacific basin equity markets," Emerging Markets Review, Elsevier, vol. 18(C), pages 123-140.
    51. Mark J. Jensen & John M. Maheu, 2014. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," Working Paper series 31_14, Rimini Centre for Economic Analysis.
    52. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Post-Print halshs-00460461, HAL.
    53. Emre Alper, C. & Fendoglu, Salih & Saltoglu, Burak, 2012. "MIDAS volatility forecast performance under market stress: Evidence from emerging stock markets," Economics Letters, Elsevier, vol. 117(2), pages 528-532.
    54. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
    55. Ashby, M. & Linton, O. B., 2022. "Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns?," Cambridge Working Papers in Economics 2259, Faculty of Economics, University of Cambridge.
    56. John M Maheu & Thomas H McCurdy, 2008. "Do high-frequency measures of volatility improve forecasts of return distributions?," Working Papers tecipa-324, University of Toronto, Department of Economics.
    57. Vozlyublennaia, Nadia & Meshcheryakov, Artem, 2014. "Dynamic correlation structure and security risk," Journal of Economics and Business, Elsevier, vol. 73(C), pages 48-64.
    58. Ernst Konrad, 2009. "The impact of monetary policy surprises on asset return volatility: the case of Germany," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(2), pages 111-135, June.
    59. Maio, Paulo, 2016. "Cross-sectional return dispersion and the equity premium," Journal of Financial Markets, Elsevier, vol. 29(C), pages 87-109.
    60. Bai, Yiyi & Okullo, Samuel J., 2023. "Drivers and pass-through of the EU ETS price: Evidence from the power sector," Energy Economics, Elsevier, vol. 123(C).
    61. Kiseok Nam & Joshua Krausz & Augustine C. Arize, 2014. "Revisiting the intertemporal risk-return relation: asymmetrical effect of unexpected volatility shocks," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2193-2203, December.
    62. Ekaterina Smetanina, 2017. "Real-Time GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 561-601.
    63. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2014. "The Impact of Oil Price Shocks on the Stock Market Return and Volatility Relationship," CAMA Working Papers 2014-71, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    64. Juan M. Londono & Nancy R. Xu, 2019. "Variance Risk Premium Components and International Stock Return Predictability," International Finance Discussion Papers 1247, Board of Governors of the Federal Reserve System (U.S.).
    65. Bernardo K. Pagnoncelli & Domingo Ramírez & Hamed Rahimian & Arturo Cifuentes, 2023. "A Synthetic Data-Plus-Features Driven Approach for Portfolio Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 187-204, June.
    66. Marine Carrasco & Barbara Rossi, 2016. "In-Sample Inference and Forecasting in Misspecified Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 313-338, July.
    67. Hui Guo & Jason Higbee & Christopher J. Neely, 2006. "Foreign exchange volatility is priced in equities," Working Papers 2004-029, Federal Reserve Bank of St. Louis.
    68. Guillaume Bagnarosa & Mark Cummins & Michael Dowling & Fearghal Kearney, 2022. "Commodity risk in European dairy firms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 151-181.
    69. Getachew, Yoseph Yilma, 2016. "Credit constraints, growth and inequality dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 364-376.
    70. Hunjra, Ahmed Imran & Azam, Muhammad & Niazi, Ghulam Shabbir Khan & Butt, Babar Zaheer & Rehman, Kashif-Ur- & Azam, Rauf i, 2010. "Risk and return relationship in stock market and commodity prices: a comprehensive study of Pakistani markets," MPRA Paper 40662, University Library of Munich, Germany.
    71. Guo, Hui & Savickas, Robert, 2006. "Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 43-56, January.
    72. Ghysels, Eric & Guérin, Pierre & Marcellino, Massimiliano, 2014. "Regime switches in the risk–return trade-off," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 118-138.
    73. Jyri Kinnunen & Minna Martikainen, 2017. "Dynamic Autocorrelation and International Portfolio Allocation," Multinational Finance Journal, Multinational Finance Journal, vol. 21(1), pages 21-48, March.
    74. Gopal K. Basak & Ravi Jagannathan & Tongshu Ma, 2004. "A Jackknife Estimator for Tracking Error Variance of Optimal Portfolios Constructed Using Estimated Inputs1," NBER Working Papers 10447, National Bureau of Economic Research, Inc.
    75. 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).
    76. Kannyiri Thadious Banyen & Joseph Kofi Nkuah, 2015. "Limited Stock Market Participation in Ghana: A Behavioral Explanation," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 3(6), pages 286-305, June.
    77. Kinnunen, Jyri, 2014. "Risk-return trade-off and serial correlation: Do volume and volatility matter?," Journal of Financial Markets, Elsevier, vol. 20(C), pages 1-19.
    78. Kambouroudis, Dimos S. & McMillan, David G., 2015. "Is there an ideal in-sample length for forecasting volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 114-137.
    79. Ioannis Chalkiadakis & Gareth W. Peters & Matthew Ames, 2023. "Hybrid ARDL-MIDAS-Transformer time-series regressions for multi-topic crypto market sentiment driven by price and technology factors," Digital Finance, Springer, vol. 5(2), pages 295-365, June.
    80. Foroni, Claudia & Marcellino, Massimiliano & Schumacher, Christian, 2011. "U-MIDAS: MIDAS regressions with unrestricted lag polynomials," Discussion Paper Series 1: Economic Studies 2011,35, Deutsche Bundesbank.
    81. Ghysels, Eric & Ball, Ryan & Zhou, Huan, 2014. "Can we Automate Earnings Forecasts and Beat Analysts?," CEPR Discussion Papers 10186, C.E.P.R. Discussion Papers.
    82. 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.
    83. 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.
    84. León Valle Ángel & Nave Pineda Juan & Rubio Irigoyen Gonzalo, 2005. "The Relationship between Risk and Expected Return in Europe," Working Papers 201025, Fundacion BBVA / BBVA Foundation.
    85. Osman Kilic & Joseph M. Marks & Kiseok Nam, 2022. "Predictable asset price dynamics, risk-return tradeoff, and investor behavior," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 749-791, August.
    86. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
    87. Jim Hanly, 2017. "Managing Energy Price Risk using Futures Contracts: A Comparative Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    88. Bali, Turan G. & Cakici, Nusret & Chabi-Yo, Fousseni, 2015. "A new approach to measuring riskiness in the equity market: Implications for the risk premium," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 101-117.
    89. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    90. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    91. Gui, Zhengqing & Huang, Yangguang & Zhao, Xiaojian, 2021. "Whom to educate? Financial literacy and investor awareness," China Economic Review, Elsevier, vol. 67(C).
    92. Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
    93. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    94. Santa-Clara, Pedro & Yan, Shu, 2004. "Jump and Volatility Risk and Risk Premia: A New Model and Lessons from S&P 500 Options," University of California at Los Angeles, Anderson Graduate School of Management qt5dv8v999, Anderson Graduate School of Management, UCLA.
    95. Cho, Sungjun, 2014. "What drives stochastic risk aversion?," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 44-63.
    96. Eva Ferreira & Mónica Gago & Angel León & Gonzalo Rubio, 2005. "An empirical comparison of the performance of alternative option pricing models," Investigaciones Economicas, Fundación SEPI, vol. 29(3), pages 483-523, September.
    97. Ang, Andrew & Liu, Jun, 2007. "Risk, return, and dividends," Journal of Financial Economics, Elsevier, vol. 85(1), pages 1-38, July.
    98. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2015. "Fundamentals and the Volatility of Real Estate Prices in China: A Sequential Modelling Strategy," Working Papers 222015, Hong Kong Institute for Monetary Research.
    99. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    100. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    101. Zhihui Lv & Amanda M. Y. Chu & Wing Keung Wong & Thomas C. Chiang, 2021. "The maximum-return-and-minimum-volatility effect: evidence from choosing risky and riskless assets to form a portfolio," Risk Management, Palgrave Macmillan, vol. 23(1), pages 97-122, June.
    102. Bali, Turan G., 2008. "The intertemporal relation between expected returns and risk," Journal of Financial Economics, Elsevier, vol. 87(1), pages 101-131, January.
    103. Marcellino, Massimiliano & Foroni, Claudia & Casarin, Roberto & Ravazzolo, Francesco, 2017. "Uncertainty Through the Lenses of A Mixed-Frequency Bayesian Panel Markov Switching Model," CEPR Discussion Papers 12339, C.E.P.R. Discussion Papers.
    104. Valadkhani, Abbas & Smyth, Russell, 2018. "Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes," Energy Economics, Elsevier, vol. 69(C), pages 89-100.
    105. Ghosh, Anisha & Linton, Oliver, 2007. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," LSE Research Online Documents on Economics 24506, London School of Economics and Political Science, LSE Library.
    106. Felix Holzmeister & Jürgen Huber & Michael Kirchler & Florian Lindner & Utz Weitzel & Stefan Zeisberger, 2019. "What Drives Risk Perception? A Global Survey withFinancial Professionals and Lay People," Working Papers 2019-05, Faculty of Economics and Statistics, Universität Innsbruck.
    107. Tobias Adrian & Richard K. Crump & Erik Vogt, 2019. "Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds," Journal of Finance, American Finance Association, vol. 74(4), pages 1931-1973, August.
    108. Pollet, Joshua M. & Wilson, Mungo, 2010. "Average correlation and stock market returns," Journal of Financial Economics, Elsevier, vol. 96(3), pages 364-380, June.
    109. Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    110. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    111. Kumari Ranjita & Kumar Nishant, 2020. "Ownership Structure and the Risk: Analysis of Indian Firms," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 8(1), pages 39-52, October.
    112. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
    113. 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.
    114. Ali F. Darrat & Bin Li & Omar Benkato, 2011. "The Relationship between Volatility and Expected Returns: Some Evidence for Australia," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 10(1), pages 27-43, April.
    115. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    116. Hui Guo & Robert Savickas, 2006. "The relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns in G7 countries," Working Papers 2006-036, Federal Reserve Bank of St. Louis.
    117. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.
    118. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    119. Xingchen Lv & Jun Meng & Qiufeng Wu, 2022. "Dynamic Influence of Network Public Opinions on Price Fluctuation of Small Agricultural Products Based on NLP-TVP-VAR Model—Taking Garlic as an Example," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    120. Cotter, John & Hanly, Jim, 2010. "Time-varying risk aversion: An application to energy hedging," Energy Economics, Elsevier, vol. 32(2), pages 432-441, March.
    121. Dave Berger & H. J. Turtle, 2009. "Time Variability In Market Risk Aversion," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 285-307, September.
    122. Jan Schulz & Mishael Milaković, 2023. "How Wealthy are the Rich?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(1), pages 100-123, March.
    123. Söhnke M. Bartram & Gregory Brown & René M. Stulz, 2017. "Why Does Idiosyncratic Risk Increase with Market Risk?," CESifo Working Paper Series 6560, CESifo.
    124. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    125. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    126. Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018. "Nowcasting GDP Growth by Reading Newspapers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205161, HAL.
    127. Seo, Sung Won & Kim, Jun Sik, 2015. "The information content of option-implied information for volatility forecasting with investor sentiment," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 106-120.
    128. Andreou, Christoforos K. & Lambertides, Neophytos & Savvides, Andreas, 2020. "Sovereign credit risk and global equity fund returns in emerging markets," Journal of International Money and Finance, Elsevier, vol. 107(C).
    129. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    130. Kanas, Angelos, 2012. "Modelling the risk–return relation for the S&P 100: The role of VIX," Economic Modelling, Elsevier, vol. 29(3), pages 795-809.
    131. Rachidi Kotchoni, 2018. "Detecting and Measuring Nonlinearity," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    132. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
    133. Wu, Shue-Jen & Lee, Wei-Ming, 2015. "Intertemporal risk–return relationships in bull and bear markets," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 308-325.
    134. Hui Guo & Robert Savickas, 2006. "Aggregate idiosyncratic volatility in G7 countries," Working Papers 2004-027, Federal Reserve Bank of St. Louis.
    135. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    136. Xingchen Lv & Weijun Lin & Jun Meng & Linan Mo, 2024. "Spillover Effect of Network Public Opinion on Market Prices of Small-Scale Agricultural Products," Mathematics, MDPI, vol. 12(4), pages 1-17, February.
    137. Matthew Spiegel & Xiaotong Wang, 2005. "Cross-sectional Variation in Stock Returns: Liquidity and Idiosyncratic Risk," Yale School of Management Working Papers amz2540, Yale School of Management, revised 01 Mar 2006.
    138. Laurent Ferrara & Dominique Guégan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 186-199.
    139. Santiago Etchegaray Alvarez, 2022. "Proyecciones macroeconómicas con datos en frecuencias mixtas. Modelos ADL-MIDAS, U-MIDAS y TF-MIDAS con aplicaciones para Uruguay," Documentos de trabajo 2022004, Banco Central del Uruguay.
    140. Thuy Thi Thu Truong & Jungmu Kim, 2019. "Premiums for Non-Sustainable and Sustainable Components of Market Volatility: Evidence from the Korean Stock Market," Sustainability, MDPI, vol. 11(18), pages 1-15, September.
    141. Emiliano Magrini & Ayca Donmez, 2013. "Agricultural Commodity Price Volatility and Its Macroeconomic Determinants: A GARCH-MIDAS Approach," JRC Research Reports JRC84138, Joint Research Centre.
    142. Müller, Gernot & Durand, Robert B. & Maller, Ross A., 2011. "The risk-return tradeoff: A COGARCH analysis of Merton's hypothesis," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 306-320, March.
    143. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    144. Malamud, Semyon & Vilkov, Grigory, 2018. "Non-myopic betas," Journal of Financial Economics, Elsevier, vol. 129(2), pages 357-381.
    145. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou & Weining Wang, 2017. "Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing," CREATES Research Papers 2017-34, Department of Economics and Business Economics, Aarhus University.
    146. John Cotter & Jim Hanly, 2014. "Performance of Utility Based Hedges," Working Papers 201404, Geary Institute, University College Dublin.
    147. Maake, Tebogo & Bonga-Bonga, Lumengo, 2019. "The relationship between carry trade and asset markets in South Africa," MPRA Paper 96667, University Library of Munich, Germany.
    148. Biswas, Anindya, 2014. "The output gap and expected security returns," Review of Financial Economics, Elsevier, vol. 23(3), pages 131-140.
    149. 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.
    150. Jianjian Jin, 2013. "Jump-Diffusion Long-Run Risks Models, Variance Risk Premium and Volatility Dynamics," Staff Working Papers 13-12, Bank of Canada.
    151. Jeong‐Hoon Kim & Jungwoo Lee & Song‐Ping Zhu & Seok‐Hyon Yu, 2014. "A multiscale correction to the Black–Scholes formula," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 30(6), pages 753-765, November.
    152. Eric Girardin & Roselyne Joyeux, 2013. "Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach," Post-Print hal-01499615, HAL.
    153. Jennie Bai & Turan G. Bali & Quan Wen, 2019. "Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence," NBER Working Papers 25995, National Bureau of Economic Research, Inc.
    154. 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).
    155. Jia, Yun & Yang, Chunpeng, 2017. "Disagreement and the risk-return relation," Economic Modelling, Elsevier, vol. 64(C), pages 97-104.
    156. Fady Barsoum & Sandra Stankiewicz, 2013. "Forecasting GDP Growth Using Mixed-Frequency Models With Switching Regimes," Working Paper Series of the Department of Economics, University of Konstanz 2013-10, Department of Economics, University of Konstanz.
    157. Ioannis Kasparis & Peter C.B. Phillips, 2009. "Dynamic Misspecification in Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 1700, Cowles Foundation for Research in Economics, Yale University.
    158. Hui Guo & Christopher J. Neely, 2006. "Investigating the intertemporal risk-return relation in international stock markets with the component GARCH model," Working Papers 2006-006, Federal Reserve Bank of St. Louis.
    159. Bai, Jennie & Bali, Turan G. & Wen, Quan, 2021. "Is there a risk-return tradeoff in the corporate bond market? Time-series and cross-sectional evidence," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1017-1037.
    160. Chari, Murali D.R. & David, Parthiban & Duru, Augustine & Zhao, Yijiang, 2019. "Bowman's risk-return paradox: An agency theory perspective," Journal of Business Research, Elsevier, vol. 95(C), pages 357-375.
    161. Kunst, Robert M. & Franses, Philip Hans, 2010. "Asymmetric Time Aggregation and its Potential Benefits for Forecasting Annual Data," Economics Series 252, Institute for Advanced Studies.
    162. Jiranyakul, Komain, 2011. "On the Risk-Return Tradeoff in the Stock Exchange of Thailand: New Evidence," MPRA Paper 45583, University Library of Munich, Germany.
    163. Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
    164. Thomas C. Chiang & Jiandong Li, 2012. "Stock Returns and Risk: Evidence from Quantile," JRFM, MDPI, vol. 5(1), pages 1-39, December.
    165. Ernest Gyapong & Daniel Gyimah & Ammad Ahmed, 2021. "Religiosity, borrower gender and loan losses in microfinance institutions: a global evidence," Review of Quantitative Finance and Accounting, Springer, vol. 57(2), pages 657-692, August.
    166. Benoît Sévi, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Post-Print hal-01500860, HAL.
    167. Esben Hedegaard & Robert J. Hodrick, 2014. "Estimating the Risk-Return Trade-off with Overlapping Data Inference," NBER Working Papers 19969, National Bureau of Economic Research, Inc.
    168. Byrne, Joseph P. & Sakemoto, Ryuta, 2021. "The conditional volatility premium on currency portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    169. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    170. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
    171. Kanas, Angelos & Molyneux, Philip, 2020. "Do measures of systemic risk predict U.S. corporate bond default rates?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    172. Imma Valentina Curato & Simona Sanfelici, 2019. "Stochastic leverage effect in high-frequency data: a Fourier based analysis," Papers 1910.06660, arXiv.org, revised Mar 2021.
    173. Salamaliki, Paraskevi K. & Venetis, Ioannis A., 2013. "Energy consumption and real GDP in G-7: Multi-horizon causality testing in the presence of capital stock," Energy Economics, Elsevier, vol. 39(C), pages 108-121.
    174. Martin Ewen, 2018. "Where is the Risk Reward? The Impact of Volatility-Based Fund Classification on Performance," Risks, MDPI, vol. 6(3), pages 1-20, August.
    175. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
    176. Joseph, Byrne & Sakemoto, Ryuta, 2020. "The Conditional Risk and Return Trade-Off on Currency Portfolios," MPRA Paper 99497, University Library of Munich, Germany.
    177. Hui Guo & Zijun Wang & Jian Yang, 2006. "Does aggregate relative risk aversion change countercyclically over time? evidence from the stock market," Working Papers 2006-047, Federal Reserve Bank of St. Louis.
    178. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    179. Wu, Jie & Zhao, Ruizeng & Sun, Jiasen & Zhou, Xuewei, 2023. "Impact of geopolitical risks on oil price fluctuations: Based on GARCH-MIDAS model," Resources Policy, Elsevier, vol. 85(PB).
    180. He, Zhifang, 2022. "Asymmetric impacts of individual investor sentiment on the time-varying risk-return relation in stock market," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 177-194.
    181. Hoerova, Marie & Bekaert, Geert, 2014. "The VIX, the variance premium and stock market volatility," Working Paper Series 1675, European Central Bank.
    182. 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.
    183. Viceira, Luis M., 2012. "Bond risk, bond return volatility, and the term structure of interest rates," International Journal of Forecasting, Elsevier, vol. 28(1), pages 97-117.
    184. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    185. Christoffersen, Peter F. & Diebold, Francis X., 2003. "Financial asset returns, direction-of-change forecasting, and volatility dynamics," CFS Working Paper Series 2004/08, Center for Financial Studies (CFS).
    186. Lee Jihyun & Kim Tong S & Lee Hoe Kyung, 2010. "Return-Volatility Relationship in High Frequency Data: Multiscale Horizon Dependency," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-43, December.
    187. Cathy Yi†Hsuan Chen & Thomas C. Chiang, 2016. "Empirical Analysis of the Intertemporal Relationship between Downside Risk and Expected Returns: Evidence from Time†varying Transition Probability Models," European Financial Management, European Financial Management Association, vol. 22(5), pages 749-796, November.
    188. Yin, Libo & Zhou, Yimin, 2016. "What drives long-term oil market volatility? Fundamentals versus Speculation," Economics Discussion Papers 2016-2, Kiel Institute for the World Economy (IfW Kiel).
    189. Cenedese, Gino & Sarno, Lucio & Tsiakas, Ilias, 2014. "Foreign exchange risk and the predictability of carry trade returns," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 302-313.
    190. Turan Bali & Kamil Yilmaz, 2009. "The Intertemporal Relation between Expected Return and Risk on Currency," Koç University-TUSIAD Economic Research Forum Working Papers 0909, Koc University-TUSIAD Economic Research Forum, revised Nov 2009.
    191. Jiang, Cuixia & Ding, Xiaoyi & Xu, Qifa & Tong, Yongbo, 2020. "A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    192. 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.
    193. Till Strohsal & Enzo Weber, 2014. "Mean-variance cointegration and the expectations hypothesis," Quantitative Finance, Taylor & Francis Journals, vol. 14(11), pages 1983-1997, November.
    194. Kim, Jun Sik & Ryu, Doojin & Seo, Sung Won, 2014. "Investor sentiment and return predictability of disagreement," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 166-178.
    195. 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.
    196. Belén Nieto & Alfonso Novales Cinca & Gonzalo Rubio, 2014. "Macroeconomic and Financial Determinants of the Volatility of Corporate Bond Returns," Documentos de Trabajo del ICAE 2014-25, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    197. 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).
    198. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    199. Pan, Beier, 2023. "The asymmetric dynamics of stock–bond liquidity correlation in China: The role of macro-financial determinants," Economic Modelling, Elsevier, vol. 124(C).
    200. Cotter, John & Hanly, Jim, 2012. "A utility based approach to energy hedging," Energy Economics, Elsevier, vol. 34(3), pages 817-827.
    201. Abdul Rashid & Saba Kausar, 2019. "Testing the Monthly Calendar Anomaly of Stock Returns in Pakistan: A Stochastic Dominance Approach," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 58(1), pages 83-104.
    202. Aslanidis, Nektarios & Christiansen, Charlotte & Savva, Christos S., 2016. "Risk-return trade-off for European stock markets," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 84-103.
    203. Jahan-Parvar, Mohammad R. & Mohammadi, Hassan, 2013. "Risk and return in the Tehran stock exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(3), pages 238-256.
    204. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.
    205. Michal Franta & David Havrlant & Marek Rusnak, 2014. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers 2014/08, Czech National Bank.
    206. Jyri Kinnunen & Minna Martikainen, 2017. "Expected Returns and Idiosyncratic Risk: Industry-Level Evidence from Russia," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(11), pages 2528-2544, November.
    207. Polzin, Friedemann & Egli, Florian & Steffen, Bjarne & Schmidt, Tobias S., 2019. "How do policies mobilize private finance for renewable energy?—A systematic review with an investor perspective," Applied Energy, Elsevier, vol. 236(C), pages 1249-1268.
    208. Jang, Jeewon & Kang, Jangkoo, 2017. "An intertemporal CAPM with higher-order moments," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 314-337.
    209. Pentti Saikkonen & Markku Lanne, 2004. "A Skewed GARCH-in-Mean Model: An Application to U.S. Stock Returns," Econometric Society 2004 North American Summer Meetings 469, Econometric Society.
    210. Lee, Kiryoung & Choi, Eunseon & Kim, Minki, 2023. "Twitter-based Chinese economic policy uncertainty," Finance Research Letters, Elsevier, vol. 53(C).
    211. Londono Yarce, J.M., 2011. "Essays on asset pricing," Other publications TiSEM 744a2ac5-7ada-4fa8-a7aa-e, Tilburg University, School of Economics and Management.
    212. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2005. "Testing the forecasting performace of IBEX 35 option implied risk neutral densities," Working Papers 0504, Banco de España.
    213. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    214. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    215. Octavio Portolano Machado & Adriana Bruscato Bortoluzzo & Sérgio Ricardo Martins & Antonio Zoratto Sanvicente, 2013. "Inter-temporal CAPM: an empirical test with Brazilian market data," Brazilian Review of Finance, Brazilian Society of Finance, vol. 11(2), pages 149-180.
    216. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Post-Print halshs-04344131, HAL.
    217. Herold, Michael & Kanz, Andreas & Muck, Matthias, 2021. "Do opinion polls move stock prices? Evidence from the US presidential election in 2016," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 665-690.
    218. Shirley J. Huang & Qianqiu Liu & Jun Yu, 2007. "Realized Daily Variance of S&P 500 Cash Index: A Revaluation of Stylized Facts," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 33-56, May.
    219. Kinnunen, Jyri, 2017. "Dynamic cross-autocorrelation in stock returns," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 162-173.
    220. Hui Guo & Robert Savickas & Zijun Wang & Jian Yang, 2006. "Is value premium a proxy for time-varying investment opportunities: some time series evidence," Working Papers 2005-026, Federal Reserve Bank of St. Louis.
    221. Kim, Eung-Bin & Byun, Suk-Joon, 2021. "Risk, ambiguity, and equity premium: International evidence," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 321-335.
    222. Wang, Zijun & Khan, M. Moosa, 2017. "Market states and the risk-return tradeoff," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 314-327.
    223. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yu, Keming, 2020. "Mixed data sampling expectile regression with applications to measuring financial risk," Economic Modelling, Elsevier, vol. 91(C), pages 469-486.
    224. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in finite order," CeMMAP working papers 53/16, Institute for Fiscal Studies.
    225. Kiseok Nam & Shahriar Khaksari & Moonsoo Kang, 2017. "Trend in aggregate idiosyncratic volatility," Review of Financial Economics, John Wiley & Sons, vol. 35(1), pages 11-28, November.
    226. Bhattacharya, Abhi & Misra, Shekhar & Sardashti, Hanieh, 2019. "Strategic orientation and firm risk," International Journal of Research in Marketing, Elsevier, vol. 36(4), pages 509-527.
    227. Cedric Okou & Eric Jacquier, 2014. "Horizon Effect in the Term Structure of Long-Run Risk-Return Trade-Offs," CIRANO Working Papers 2014s-36, CIRANO.
    228. Tariq Aziz & Valeed Ahmad Ansari, 2017. "Idiosyncratic volatility and stock returns: Indian evidence," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1420998-142, January.
    229. Andreou, Elena & Kasparis, Ioannis & Phillips, Peter C. B., 2013. "Nonparametric Predictive Regression," CEPR Discussion Papers 9570, C.E.P.R. Discussion Papers.
    230. Ashby, M. & Linton, O. B., 2022. "Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns?," Janeway Institute Working Papers 2226, Faculty of Economics, University of Cambridge.
    231. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    232. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    233. Kanniainen, Juho & Piché, Robert, 2013. "Stock price dynamics and option valuations under volatility feedback effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 722-740.
    234. Tobias Adrian & Joshua V. Rosenberg, 2006. "Stock returns and volatility: pricing the short-run and long-run components of market risk," Staff Reports 254, Federal Reserve Bank of New York.
    235. Wang, Jianxin & Yang, Minxian, 2013. "On the risk return relationship," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 132-141.
    236. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    237. Miguel A. Ferreira & Pedro Santa-Clara, 2008. "Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole," NBER Working Papers 14571, National Bureau of Economic Research, Inc.
    238. Chang, Kuang-Liang, 2016. "Does the return-state-varying relationship between risk and return matter in modeling the time series process of stock return?," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 72-87.
    239. 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.
    240. 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.
    241. Wang, Wenzhao, 2021. "The mean–variance relation: A 24-hour story," Economics Letters, Elsevier, vol. 208(C).
    242. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    243. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
    244. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," EconomiX Working Papers 2019-14, University of Paris Nanterre, EconomiX.
    245. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
    246. Fung, Derrick W.H. & Lee, Wing Yan & Yang, Charles C. & Yeh, Jason J.H., 2024. "Risk taking, performance, and resilience to the COVID-19 pandemic: Evidence from public property-casualty insurers," International Review of Financial Analysis, Elsevier, vol. 91(C).
    247. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
    248. 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.
    249. Miralles-Marcelo, José Luis & Miralles-Quirós, María del Mar & Miralles-Quirós, José Luis, 2012. "Asset pricing with idiosyncratic risk: The Spanish case," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 261-271.
    250. Anthony W. Lynch & Jessica A. Wachter, 2008. "Using Samples of Unequal Length in Generalized Method of Moments Estimation," NBER Working Papers 14411, National Bureau of Economic Research, Inc.
    251. Dimitrios Koutmos, 2015. "Is there a Positive Risk†Return Tradeoff? A Forward†Looking Approach to Measuring the Equity Premium," European Financial Management, European Financial Management Association, vol. 21(5), pages 974-1013, November.
    252. Hao Liu & Shihan Shen & Tianyi Wang & Zhuo Huang, 2016. "Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect," China Economic Journal, Taylor & Francis Journals, vol. 9(2), pages 140-153, May.
    253. Shanken, Jay & Tamayo, Ane, 2012. "Payout yield, risk, and mispricing: A Bayesian analysis," Journal of Financial Economics, Elsevier, vol. 105(1), pages 131-152.
    254. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    255. 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.
    256. Xianning WANG & Jingrong DONG & Zhi XIAO & Guanjie HE, 2019. "A novel spatial mixed frequency forecasting model with application to Chinese regional GDP," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 54-77, June.
    257. Eric Jacquier & Cedric Okou, 2013. "Disentangling Continuous Volatility from Jumps in Long-Run Risk-Return Relationships," CIRANO Working Papers 2013s-14, CIRANO.
    258. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    259. Mili, Mehdi, 2019. "The impact of tradeoff between risk and return on mean reversion in sovereign CDS markets," Research in International Business and Finance, Elsevier, vol. 48(C), pages 187-200.
    260. Bandi, Federico M. & Perron, Benoît, 2008. "Long-run risk-return trade-offs," Journal of Econometrics, Elsevier, vol. 143(2), pages 349-374, April.
    261. Gregory Connor & Anita Suurlaht, 2012. "Dynamic Stock Market Covariances in the Eurozone," Economics Department Working Paper Series n222-12.pdf, Department of Economics, National University of Ireland - Maynooth.
    262. Hossein Asgharian & Charlotte Christiansen & Rangan Gupta & Ai Jun Hou, 2016. "Effects of Economic Policy Uncertainty Shocks on the Long-Run US-UK Stock Market Correlation," CREATES Research Papers 2016-29, Department of Economics and Business Economics, Aarhus University.
    263. Vít Pošta & Zdeněk Pikhart, 2015. "Financial Risk and Real Variables: Evidence Based on a SVAR Analysis of the Czech Economy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(5), pages 516-537.
    264. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2013. "Testing for Granger Causality with Mixed Frequency Data," CEPR Discussion Papers 9655, C.E.P.R. Discussion Papers.
    265. Jiang, Xiaoquan & Lee, Bong-Soo, 2014. "The intertemporal risk-return relation: A bivariate model approach," Journal of Financial Markets, Elsevier, vol. 18(C), pages 158-181.
    266. 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).
    267. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
    268. 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.
    269. Gerrit Reher & Bernd Wilfling, 2016. "A nesting framework for Markov-switching GARCH modelling with an application to the German stock market," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 411-426, March.
    270. Bonino-Gayoso, Nicolás & García-Hiernaux, Alfredo, 2019. "TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables," MPRA Paper 93366, University Library of Munich, Germany.
    271. Eric Ghysels & Alberto Plazzi & Rossen Valkanov, 2007. "Valuation in US Commercial Real Estate," European Financial Management, European Financial Management Association, vol. 13(3), pages 472-497, June.
    272. Okou, Cédric & Jacquier, Éric, 2016. "Horizon effect in the term structure of long-run risk-return trade-offs," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 445-466.
    273. Choe, Kwang-il & Choi, Pilsun & Nam, Kiseok & Vahid, Farshid, 2012. "Testing financial contagion on heteroskedastic asset returns in time-varying conditional correlation," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 271-291.
    274. Koutmos, Gregory & Knif, Johan & Philippatos, George C., 2008. "Modeling common volatility characteristics and dynamic risk premia in European equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(3), pages 567-578, August.
    275. Freitag L., 2014. "Default probabilities, CDS premiums and downgrades : A probit-MIDAS analysis," Research Memorandum 038, Maastricht University, Graduate School of Business and Economics (GSBE).
    276. 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.
    277. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    278. Neaime, Simon, 2012. "The global financial crisis, financial linkages and correlations in returns and volatilities in emerging MENA stock markets," Emerging Markets Review, Elsevier, vol. 13(3), pages 268-282.
    279. Manh Cuong Nguyen & Viet Anh Dang & Tri Tri Nguyen, 2023. "The transfer of risk taking along the supply chain," Review of Quantitative Finance and Accounting, Springer, vol. 61(4), pages 1341-1378, November.
    280. Jin, Xing & Wang, Leping & Yu, Jun, 2007. "Temporal aggregation and risk-return relation," Finance Research Letters, Elsevier, vol. 4(2), pages 104-115, June.
    281. Khoo, Joye & Cheung, Adrian (Wai Kong), 2021. "Does geopolitical uncertainty affect corporate financing? Evidence from MIDAS regression," Global Finance Journal, Elsevier, vol. 47(C).
    282. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2018. "Downside risk and stock returns in the G7 countries: An empirical analysis of their long-run and short-run dynamics," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 21-32.
    283. Alper, C. Emre & Fendoglu, Salih & Saltoglu, Burak, 2008. "Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets," MPRA Paper 7460, University Library of Munich, Germany.
    284. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    285. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
    286. Guo, Hui & Qiu, Buhui, 2014. "Options-implied variance and future stock returns," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 93-113.
    287. Jonathan Readshaw & Stefano Giani, 2020. "Using Company Specific Headlines and Convolutional Neural Networks to Predict Stock Fluctuations," Papers 2006.12426, arXiv.org.
    288. Til Schuermann & Kevin J. Stiroh, 2006. "Visible and hidden risk factors for banks," Staff Reports 252, Federal Reserve Bank of New York.
    289. Hui Guo & Robert Savickas, 2006. "Idiosyncratic volatility, economic fundamentals, and foreign exchange rates," Working Papers 2005-025, Federal Reserve Bank of St. Louis.
    290. Wang, Wenzhao, 2018. "The mean–variance relation and the role of institutional investor sentiment," Economics Letters, Elsevier, vol. 168(C), pages 61-64.
    291. Baele, Lieven & Londono, Juan M., 2013. "Understanding industry betas," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 30-51.
    292. Benoît Sévi & César Baena, 2013. "The explanatory power of signed jumps for the risk-return tradeoff," Economics Bulletin, AccessEcon, vol. 33(2), pages 1029-1046.
    293. Ederington, Louis H. & Guan, Wei, 2010. "How asymmetric is U.S. stock market volatility?," Journal of Financial Markets, Elsevier, vol. 13(2), pages 225-248, May.
    294. Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
    295. 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.
    296. DasGupta, Ranjan & Deb, Soumya G., 2022. "Role of corporate governance in moderating the risk-return paradox: Cross country evidence," Journal of Contemporary Accounting and Economics, Elsevier, vol. 18(2).
    297. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 698-721.
    298. Aghamolla, Cyrus & An, Byeong-Je, 2021. "Voluntary disclosure with evolving news," Journal of Financial Economics, Elsevier, vol. 140(1), pages 21-53.
    299. Cláudia Duarte, 2016. "A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data," Working Papers w201601, Banco de Portugal, Economics and Research Department.
    300. Semih Emre Çekin & Victor J. Valcarcel, 2020. "Inflation volatility and inflation in the wake of the great recession," Empirical Economics, Springer, vol. 59(4), pages 1997-2015, October.
    301. Nyberg, Henri, 2010. "QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles," MPRA Paper 23724, University Library of Munich, Germany.
    302. Apergis, Nicholas, 2015. "Newswire messages and sovereign credit ratings: Evidence from European countries under austerity reform programmes," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 54-62.
    303. Salvador, Enrique & Floros, Christos & Arago, Vicent, 2014. "Re-examining the risk–return relationship in Europe: Linear or non-linear trade-off?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 60-77.
    304. Chen Xilong & Ghysels Eric & Wang Fangfang, 2011. "HYBRID GARCH Models and Intra-Daily Return Periodicity," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-28, February.
    305. Jiawen Xu & Yixuan Li & Kai Liu & Tao Chen, 2023. "Portfolio selection: from under-diversification to concentration," Empirical Economics, Springer, vol. 64(4), pages 1539-1557, April.
    306. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    307. Serena Ng & Susannah Scanlan, 2023. "Constructing High Frequency Economic Indicators by Imputation," Papers 2303.01863, arXiv.org, revised Oct 2023.
    308. 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.
    309. Dotsis, George, 2017. "The market price of risk of the variance term structure," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 41-52.
    310. Gong, Xu & Sun, Yi & Du, Zhili, 2022. "Geopolitical risk and China's oil security," Energy Policy, Elsevier, vol. 163(C).
    311. Hui Guo & Robert Savickas, 2006. "Understanding stock return predictability," Working Papers 2006-019, Federal Reserve Bank of St. Louis.
    312. Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 521-536.
    313. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Momentum has its moments," Journal of Financial Economics, Elsevier, vol. 116(1), pages 111-120.
    314. Benoît Sévi & César Baena, 2012. "A reassessment of the risk-return tradeoff at the daily horizon," Economics Bulletin, AccessEcon, vol. 32(1), pages 190-203.
    315. Ryan T. Ball & Eric Ghysels, 2018. "Automated Earnings Forecasts: Beat Analysts or Combine and Conquer?," Management Science, INFORMS, vol. 64(10), pages 4936-4952, October.
    316. Chen, Xiaoyu & Chiang, Thomas C., 2016. "Stock returns and economic forces—An empirical investigation of Chinese markets," Global Finance Journal, Elsevier, vol. 30(C), pages 45-65.
    317. Philippe Masset & Martin Wallmeier, 2010. "A High†Frequency Investigation of the Interaction between Volatility and DAX Returns," European Financial Management, European Financial Management Association, vol. 16(3), pages 327-344, June.
    318. Umutlu, Mehmet, 2019. "Does idiosyncratic volatility matter at the global level?," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 252-268.
    319. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2013. "Conditional alphas and realized betas," Textos para discussão 341, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    320. 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.
    321. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    322. Sara Boni & Massimiliano Caporin & Francesco Ravazzolo, 2024. "Nowcasting Inflation at Quantiles: Causality from Commodities," BEMPS - Bozen Economics & Management Paper Series BEMPS102, Faculty of Economics and Management at the Free University of Bozen.
    323. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Wang, Tianyang, 2016. "An examination of the flow characteristics of crude oil: Evidence from risk-neutral moments," Energy Economics, Elsevier, vol. 54(C), pages 213-223.
    324. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    325. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
    326. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," Working Papers hal-04141871, HAL.
    327. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.
    328. Roi D. Taussig, 2017. "Stickiness of employee expenses and implications for stock returns," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 297-309, August.
    329. Christian Brownlees & Benjamin Chabot & Eric Ghysels & Christopher J. Kurz, 2015. "Backtesting Systemic Risk Measures During Historical Bank Runs," Working Paper Series WP-2015-9, Federal Reserve Bank of Chicago.
    330. Gong, Yuting & Chen, Qiang & Liang, Jufang, 2018. "A mixed data sampling copula model for the return-liquidity dependence in stock index futures markets," Economic Modelling, Elsevier, vol. 68(C), pages 586-598.
    331. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    332. Alonso, Francisco & Blanco, Roberto & Rubio Irigoyen, Gonzalo, 2005. "Option-Implied Preferences Adjustments and Risk-Neutral Density Forecasts," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    333. David P. Brown & Miguel A. Ferreira, 2016. "Idiosyncratic Volatility of Small Public Firms and Entrepreneurial Risk," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-59, March.
    334. Lanter, David & Hirsch, Stefan & Finger, Robert, 2018. "Profitability and Competition in EU Food Retailing," 2018 Annual Meeting, August 5-7, Washington, D.C. 274202, Agricultural and Applied Economics Association.
    335. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
    336. Choi, Jaewon & Richardson, Matthew, 2016. "The volatility of a firm's assets and the leverage effect," Journal of Financial Economics, Elsevier, vol. 121(2), pages 254-277.
    337. Nava, Consuelo R. & Osti, Linda & Zoia, Maria Grazia, 2022. "Forecasting Domestic Tourism across Regional Destinations through MIDAS Regressions," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202207, University of Turin.
    338. Travis L Johnson, 2019. "A Fresh Look at Return Predictability Using a More Efficient Estimator," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 9(1), pages 1-46.
    339. Bansal, Naresh & Stivers, Chris, 2022. "Bond risk’s role in the equity risk-return tradeoff," Journal of Financial Markets, Elsevier, vol. 60(C).
    340. Ryan T. Ball & Jonathan Bonham & Thomas Hemmer, 2020. "Does it pay to ‘Be Like Mike’? Aspiratonal peer firms and relative performance evaluation," Review of Accounting Studies, Springer, vol. 25(4), pages 1507-1541, December.
    341. Huang, Lin & Wang, Zijun, 2014. "Is the investment factor a proxy for time-varying investment opportunities? The US and international evidence," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 219-232.
    342. Xu, Qifa & Zhuo, Xingxuan & Jiang, Cuixia & Liu, Xi & Liu, Yezheng, 2018. "Group penalized unrestricted mixed data sampling model with application to forecasting US GDP growth," Economic Modelling, Elsevier, vol. 75(C), pages 221-236.
    343. Jianjian Jin, 2015. "Jump-Diffusion Long-Run Risks Models, Variance Risk Premium, and Volatility Dynamics," Review of Finance, European Finance Association, vol. 19(3), pages 1223-1279.
    344. Liu, Dehong & Gu, Hongmei & Lung, Peter, 2016. "The equity mispricing: Evidence from China's stock market," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 211-223.
    345. Pierpaolo Andriani & Bill McKelvey, 2009. "Perspective ---From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations," Organization Science, INFORMS, vol. 20(6), pages 1053-1071, December.
    346. Kinnunen, Jyri, 2013. "Dynamic return predictability in the Russian stock market," Emerging Markets Review, Elsevier, vol. 15(C), pages 107-121.
    347. Reschenhofer, Erhard & Mangat, Manveer Kaur & Stark, Thomas, 2020. "Volatility forecasts, proxies and loss functions," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 133-153.
    348. Dirk Swagerman & Ivan Novakovic, 2010. "Multi-National Evidence On Calendar Patterns In Stock Returns: An Empirical Case Study On Investment Strategy And The Halloween Effect," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(4), pages 23-42.
    349. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2009. "GDP nowcasting with ragged-edge data : A semi-parametric modelling," Post-Print halshs-00344839, HAL.
    350. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
    351. Cheng, Ai-Ru & Jahan-Parvar, Mohammad R. & Rothman, Philip, 2010. "An empirical investigation of stock market behavior in the Middle East and North Africa," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 413-427, June.
    352. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    353. Mathijs Cosemans & Rik Frehen & Peter C. Schotman & Rob Bauer, 2016. "Estimating Security Betas Using Prior Information Based on Firm Fundamentals," The Review of Financial Studies, Society for Financial Studies, vol. 29(4), pages 1072-1112.
    354. Yang, Chunpeng & Jia, Yun, 2016. "Buy-sell imbalance and the mean-variance relation," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 49-58.
    355. Cathy Yi-Hsuan Chen & Thomas C. Chiang & Wolfgang Karl Härdle, 2016. "Downside risk and stock returns: An empirical analysis of the long-run and short-run dynamics from the G-7 Countries," SFB 649 Discussion Papers SFB649DP2016-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    356. Laine, Olli-Matti & Lindblad, Annika, 2020. "Nowcasting Finnish GDP growth using financial variables: a MIDAS approach," BoF Economics Review 4/2020, Bank of Finland.
    357. Ryuta Sakemoto, 2018. "The intertemporal relation between expected returns and conditional correlations between precious metals and the stock market," Economics and Business Letters, Oviedo University Press, vol. 7(1), pages 24-35.
    358. Yao, Can-Zhong & Li, Min-Jian, 2023. "GARCH-MIDAS-GAS-copula model for CoVaR and risk spillover in stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    359. Huang, Teng-Ching & Wu, Ching-Chih & Lin, Bing-Huei, 2016. "Institutional herding and risk–return relationship," Journal of Business Research, Elsevier, vol. 69(6), pages 2073-2080.
    360. Hatemi-J, Abdulnasser & Irandoust, Manuchehr, 2011. "The dynamic interaction between volatility and returns in the US stock market using leveraged bootstrap simulations," Research in International Business and Finance, Elsevier, vol. 25(3), pages 329-334, September.
    361. Rafique, Amir & Iqbal, Khurram & Zakaria, Muhammad & Mujtaba, Ghulam, 2019. "Investigating ICAPM with mean-reverting dynamic conditional correlation: Evidence from an emerging stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 514-523.
    362. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yuan, Jing, 2018. "Measuring systemic risk of the banking industry in China: A DCC-MIDAS-t approach," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 13-31.
    363. Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
    364. Pedro Piccoli & Newton C. A. da Costa & Wesley Vieira da Silva & June A. W. Cruz, 2018. "Investor sentiment and the risk–return tradeoff in the Brazilian market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 599-618, November.
    365. Long Chen & Hui Guo & Lu Zhang, 2006. "Equity market volatility and expected risk premium," Working Papers 2006-007, Federal Reserve Bank of St. Louis.
    366. Michael D. Boldin & Jonathan H. Wright, 2015. "Weather-adjusting employment data," Working Papers 15-5, Federal Reserve Bank of Philadelphia.
    367. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    368. Brenner, Menachem & Izhakian, Yehuda, 2018. "Asset pricing and ambiguity: Empirical evidence⁎," Journal of Financial Economics, Elsevier, vol. 130(3), pages 503-531.
    369. Farooq Malik, 2015. "Revisiting the relationship between risk and return," Review of Quantitative Finance and Accounting, Springer, vol. 44(1), pages 25-40, January.
    370. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    371. Bali, Turan G. & Engle, Robert F., 2010. "The intertemporal capital asset pricing model with dynamic conditional correlations," Journal of Monetary Economics, Elsevier, vol. 57(4), pages 377-390, May.
    372. Chiang, Thomas C. & Li, Huimin & Zheng, Dazhi, 2015. "The intertemporal risk-return relationship: Evidence from international markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 156-180.
    373. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2006. "Option-implied preferences adjustments, density forecasts, and the equity risk premium," Working Papers 0630, Banco de España.
    374. Minxian Yang, 2014. "The Risk Return Relationship: Evidence from Index Return and Realised Variance Series," Discussion Papers 2014-16, School of Economics, The University of New South Wales.
    375. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    376. Cenesizoglu, Tolga, 2022. "Return decomposition over the business cycle," Journal of Banking & Finance, Elsevier, vol. 143(C).
    377. Chevapatrakul, Thanaset, 2013. "Return sign forecasts based on conditional risk: Evidence from the UK stock market index," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2342-2353.
    378. Curato, Imma Valentina & Sanfelici, Simona, 2022. "Stochastic leverage effect in high-frequency data: a Fourier based analysis," Econometrics and Statistics, Elsevier, vol. 23(C), pages 53-82.
    379. Vozlyublennaia, Nadia, 2013. "Do firm characteristics matter for the dynamics of idiosyncratic risk?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 35-46.
    380. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
    381. Durham, Garland B., 2007. "SV mixture models with application to S&P 500 index returns," Journal of Financial Economics, Elsevier, vol. 85(3), pages 822-856, September.
    382. Borup, Daniel & Rapach, David E. & Schütte, Erik Christian Montes, 2023. "Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1122-1144.
    383. 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.
    384. Michael William Ashby & Oliver Bruce Linton, 2024. "Do Consumption-Based Asset Pricing Models Explain the Dynamics of Stock Market Returns?," JRFM, MDPI, vol. 17(2), pages 1-42, February.
    385. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

  9. Santa-Clara, Pedro & Saretto, Alessio, 2004. "Option Strategies: Good Deals and Margin Calls," University of California at Los Angeles, Anderson Graduate School of Management qt0499w44p, Anderson Graduate School of Management, UCLA.

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    10. Duyvesteyn, Johan & de Zwart, Gerben, 2015. "Riding the swaption curve," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 57-75.
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    12. Sirio Aramonte & Mohammad Jahan-Parvar & Samuel Rosen & John W. Schindler, 2021. "Firm-specific risk-neutral distributions with options and CDS," BIS Working Papers 921, Bank for International Settlements.
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    14. Andrea Frazzini & Lasse H. Pedersen, 2012. "Embedded Leverage," NBER Working Papers 18558, National Bureau of Economic Research, Inc.
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    24. Manuel Ammann & Mathis Mörke, 2019. "Credit Variance Risk Premiums," Working Papers on Finance 1908, University of St. Gallen, School of Finance.
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    27. Joseph K.W. Fung & Eric Girardin & Jian Hua, 2022. "How does the exchange-rate regime affect dual-listed share price parity? Evidence from China’s A- and H-share markets," Post-Print hal-03821210, HAL.
    28. Pedersen, Lasse Heje & Vestergaard Jensen, Mads, 2015. "Early Option Exercise: Never Say Never," CEPR Discussion Papers 11019, C.E.P.R. Discussion Papers.
    29. Ghada Ali TIMRAZ & Faris Nasif AL-SHUBIRI, 2012. "The Impact Of Stock Options Trading On The Market Value Of Companies Listed In Kuwait Stock Exchange," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 2(3), pages 63-76, September.
    30. Amira, Khaled & Bennour, Khaled, 2010. "Borrowing Constraint and the Effect of Option Introduction," MPRA Paper 26440, University Library of Munich, Germany.
    31. George Kapetanios & Michael Neumann & George Skiadopoulos, 2014. "Jumps in Option Prices and Their Determinants: Real-time Evidence from the E-mini S&P 500 Option Market," Working Papers 730, Queen Mary University of London, School of Economics and Finance.
    32. Byun, Suk Joon & Jeon, Byoung Hyun & Min, Byungsun & Yoon, Sun-Joong, 2015. "The role of the variance premium in Jump-GARCH option pricing models," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 38-56.
    33. Kazuhiro Hiraki & George Skiadopoulos, 2018. "The Contribution of Frictions to Expected Returns," Working Papers 874, Queen Mary University of London, School of Economics and Finance.
    34. Lai, Ya-Wen, 2017. "Macroeconomic factors and index option returns," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 452-477.
    35. David Volkmann, 2021. "Explaining S&P500 option returns: an implied risk-adjusted approach," 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. 29(2), pages 665-685, June.
    36. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    37. Chin‐Ho Chen, 2021. "Investor sentiment, misreaction, and the skewness‐return relationship," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1427-1455, September.
    38. Goyal, Amit & Saretto, Alessio, 2009. "Cross-section of option returns and volatility," Journal of Financial Economics, Elsevier, vol. 94(2), pages 310-326, November.
    39. Leippold, Markus & Su, Lujing, 2015. "Collateral smile," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 15-28.
    40. Bakshi, Gurdip & Madan, Dilip & Panayotov, George, 2010. "Returns of claims on the upside and the viability of U-shaped pricing kernels," Journal of Financial Economics, Elsevier, vol. 97(1), pages 130-154, July.
    41. Oleg Sokolinskiy, 2020. "Conditional dependence in post-crisis markets: dispersion and correlation skew trades," Review of Quantitative Finance and Accounting, Springer, vol. 55(2), pages 389-426, August.
    42. Kevin Aretz & Ming-Tsung Lin & Ser-Huang Poon, 2023. "Moneyness, Underlying Asset Volatility, and the Cross-Section of Option Returns," Review of Finance, European Finance Association, vol. 27(1), pages 289-323.
    43. 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.
    44. Chang‐Mo Kang & Donghyun Kim & Junyong Kim & Geul Lee, 2022. "Informed trading of out‐of‐the‐money options and market efficiency," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(2), pages 247-279, June.
    45. Stylianos Perrakis, 2022. "From innovation to obfuscation: continuous time finance fifty years later," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 369-401, September.
    46. Augustin, Patrick & Brenner, Menachem & Grass, Gunnar & Orłowski, Piotr & Subrahmanyam, Marti G., 2023. "Informed options strategies before corporate events," Journal of Financial Markets, Elsevier, vol. 63(C).
    47. Kristoffer Andersson & Cornelis W. Oosterlee, 2023. "D-TIPO: Deep time-inconsistent portfolio optimization with stocks and options," Papers 2308.10556, arXiv.org, revised Sep 2023.
    48. Nicole Branger & Christian Schlag, 2007. "Option Betas: Risk Measures For Options," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(07), pages 1137-1157.
    49. Bernales, Alejandro & Verousis, Thanos & Voukelatos, Nikolaos, 2020. "Do investors follow the herd in option markets?," Journal of Banking & Finance, Elsevier, vol. 119(C).
    50. Bas Peeters, 2012. "Risk premiums in a simple market model for implied volatility," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 739-748, January.
    51. Augustin, Patrick & Brenner, Menachem & Grass, Gunnar & Orłowski, Piotr & Subrahmanyam, Marti G., 2022. "Informed options strategies before corporate events," LawFin Working Paper Series 39, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    52. Nikolaos Voukelatos & Thanos Verousis, 2019. "Option‐implied information and stock herding," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1429-1442, October.
    53. Longarela, Iñaki R. & Mayoral, Silvia, 2015. "Quote inefficiency in options markets," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 23-36.
    54. Jose Faias & Pedro Santa-Clara, 2011. "Optimal Option Portfolio Strategies," EcoMod2011 3041, EcoMod.
    55. Aramonte, Sirio, 2014. "Macroeconomic uncertainty and the cross-section of option returns," Journal of Financial Markets, Elsevier, vol. 21(C), pages 25-49.

  10. Cochrane, John. H. & Longstaff, Francis A. & Santa-Clara, Pedro, 2004. "Two Trees," University of California at Los Angeles, Anderson Graduate School of Management qt6mt207w2, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Coeurdacier, Nicolas & Guibaud, Stéphane, 2011. "International portfolio diversification is better than you think," Journal of International Money and Finance, Elsevier, vol. 30(2), pages 289-308, March.
    2. Sylvain, Serginio, 2014. "Does Human Capital Risk Explain The Value Premium Puzzle?," MPRA Paper 54551, University Library of Munich, Germany.
    3. Tarek Alexander Hassan, 2010. "Country Size, Currency Areas, and International Asset Returns," 2010 Meeting Papers 365, Society for Economic Dynamics.
    4. Nicolae Gârleanu & Stavros Panageas & Jianfeng Yu, 2013. "Financial Entanglement: A Theory of Incomplete Integration, Leverage, Crashes, and Contagion," NBER Working Papers 19381, National Bureau of Economic Research, Inc.
    5. Ma, Chaoqun & Wang, Hailong & Cheng, Fengchao & Hu, Duni, 2017. "Asset pricing and institutional investors with disagreements," Economic Modelling, Elsevier, vol. 64(C), pages 231-248.
    6. Harjoat Bhamra & Nicolas Coeurdacier & Stéphane Guibaud, 2014. "A Dynamic Equilibrium Model of Imperfectly Integrated Financial Markets," SciencePo Working papers Main hal-03393013, HAL.
    7. Tarek A. Hassan, 2009. "Country Size, Currency Unions, and International Asset Returns," Working Papers 154, Oesterreichische Nationalbank (Austrian Central Bank).
    8. Jeong, Daehee & Kim, Hwagyun & Park, Joon Y., 2015. "Does ambiguity matter? Estimating asset pricing models with a multiple-priors recursive utility," Journal of Financial Economics, Elsevier, vol. 115(2), pages 361-382.
    9. Hansen, Simon Lysbjerg, 2015. "Cross-sectional asset pricing with heterogeneous preferences and beliefs," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 125-151.
    10. Nikolai Roussanov, 2010. "Composition of Wealth, Conditioning Information, and the Cross-Section of Stock Returns," NBER Working Papers 16073, National Bureau of Economic Research, Inc.
    11. Nicolas Coeurdacier & Stéphane Guibaud, 2005. "A dynamic equilibrium model of imperfectly integrated financial markets," PSE Working Papers halshs-00590775, HAL.
    12. Dragana Draganac, 2017. "Do Dividend Shocks Affect Excess Returns: An Experimental Study," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 62(214), pages 45-86, June - Se.
    13. Curatola, Giuliano, 2017. "Portfolio choice and asset prices when preferences are interdependent," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 197-223.
    14. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    15. Santos, Tano & Veronesi, Pietro, 2010. "Habit formation, the cross section of stock returns and the cash-flow risk puzzle," Journal of Financial Economics, Elsevier, vol. 98(2), pages 385-413, November.
    16. Akira Yamazaki, 2015. "Asset Pricing With Non-Geometric Type Of Dividends," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-38, December.

  11. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Stylianos Asimakopoulos & Joan Paredes & Thomas Warmedinger, 2020. "Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 369-390, January.
    2. Etienne, Xiaoli, 2015. "Financialization of Agricultural Commodity Markets: Do Financial Data Help to Forecast Agricultural Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 211626, International Association of Agricultural Economists.
    3. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    4. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    5. Márcio Gomes Pinto Garcia & Marcelo Cunha Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "Economic gains of realized volatility in the Brazilian stock market," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(3), pages 319-349.
    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. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    8. Carl Bonham & Peter Fuleky & James Jones & Ashley Hirashima, 2015. "Nowcasting Tourism Industry Performance Using High Frequency Covariates," Working Papers 2015-13R, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2016.
    9. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    10. Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
    11. Prabheesh, K.P. & Sasongko, Aryo & Indawan, Fiskara, 2023. "Did the policy responses influence credit and business cycle co-movement during the COVID-19 crisis? Evidence from Indonesia," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 243-255.
    12. Özer Karagedikli & Murat Özbilgin, 2019. "Mixed in New Zealand: Nowcasting Labour Markets with MIDAS," Reserve Bank of New Zealand Analytical Notes series AN2019/04, Reserve Bank of New Zealand.
    13. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    14. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-time measurement of business conditions," International Finance Discussion Papers 901, Board of Governors of the Federal Reserve System (U.S.).
    15. Edward S. Knotek & Saeed Zaman, 2024. "Nowcasting Inflation," Working Papers 24-06, Federal Reserve Bank of Cleveland.
    16. Lixiong Yang, 2022. "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, vol. 62(2), pages 533-551, February.
    17. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    18. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    19. Kaustubh & Soumya Bhadury & Saurabh Ghosh, 2024. "Reinvigorating Gva Nowcasting In The Postpandemic Period: A Case Study For India," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 27(Spesial I), pages 95-130, Februari.
    20. Harchaoui, Tarek M. & Janssen, Robert V., 2018. "How can big data enhance the timeliness of official statistics?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 225-234.
    21. Holmes, Mark J. & Iregui, Ana María & Otero, Jesús, 2021. "The effects of FX-interventions on forecasters disagreement: A mixed data sampling view," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    22. Marina Diakonova & Luis Molina & Hannes Mueller & Javier J. Pérez & Cristopher Rauh, 2022. "The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting," Working Papers 2232, Banco de España.
    23. Raquel Nadal Cesar Gonçalves, 2022. "Nowcasting Brazilian GDP with Electronic Payments Data," Working Papers Series 564, Central Bank of Brazil, Research Department.
    24. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    25. Helena Rodríguez, 2014. "Un indicador de la evolución del PIB uruguayo en tiempo real," Documentos de trabajo 2014009, Banco Central del Uruguay.
    26. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    27. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    28. C. Emre Alper & Salih Fendoglu & Burak Saltoglu, 2009. "MIDAS Volatility Forecast Performance Under Market Stress: Evidence from Emerging and Developed Stock Markets," Working Papers 2009/04, Bogazici University, Department of Economics.
    29. Fady Barsoum, 2015. "Point and Density Forecasts Using an Unrestricted Mixed-Frequency VAR Model," Working Paper Series of the Department of Economics, University of Konstanz 2015-19, Department of Economics, University of Konstanz.
    30. Yose Rizal Damuri & Prabaning Tyas & Haryo Aswicahyono & Lionel Priyadi & Stella Kusumawardhani & Ega Kurnia Yazid, 2021. "Tracking the Ups and Downs in Indonesia’s Economic Activity During COVID-19 Using Mobility Index: Evidence from Provinces in Java and Bali," Working Papers DP-2021-18, Economic Research Institute for ASEAN and East Asia (ERIA).
    31. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    32. Cláudia Duarte, 2015. "Covariate-augmented unit root tests with mixed-frequency data," Working Papers w201507, Banco de Portugal, Economics and Research Department.
    33. 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.
    34. Gustavo Adolfo HERNANDEZ DIAZ & Margarita MARÍN JARAMILLO, 2016. "Pronóstico del Consumo Privado: Usando datos de alta frecuencia para el pronóstico de variables de baja frecuencia," Archivos de Economía 14828, Departamento Nacional de Planeación.
    35. 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.
    36. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    37. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    38. Marie Bessec, 2019. "Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data," Post-Print hal-02181552, HAL.
    39. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    40. Anthony S. Tay, 2006. "Mixing Frequencies : Stock Returns as a Predictor of Real Output Growth," Macroeconomics Working Papers 22480, East Asian Bureau of Economic Research.
    41. Hui Jun ZHANG & Jean-Marie DUFOUR & John W. GALBRAITH, 2013. "Exchange Rates and Commodity Prices : Measuring Causality at Multiple Horizons," Cahiers de recherche 14-2013, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    42. Monokroussos, George & Zhao, Yongchen, 2020. "Nowcasting in real time using popularity priors," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1173-1180.
    43. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    44. Götz, T.B. & Hecq, A.W., 2013. "Nowcasting causality in mixed frequency vector autoregressive models," Research Memorandum 050, Maastricht University, Graduate School of Business and Economics (GSBE).
    45. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    46. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
    47. Qian Chen & Xiang Gao & Shan Xie & Li Sun & Shuairu Tian & Shigeyuki Hamori, 2021. "On the Predictability of China Macro Indicator with Carbon Emissions Trading," Energies, MDPI, vol. 14(5), pages 1-24, February.
    48. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    49. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    50. Langedijk, Sven & Monokroussos, George & Papanagiotou, Evangelia, 2015. "Benchmarking Liquidity Proxies: Accounting for Dynamics and Frequency Issues," MPRA Paper 61865, University Library of Munich, Germany.
    51. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    52. Valadkhani, Abbas & Smyth, Russell, 2017. "How do daily changes in oil prices affect US monthly industrial output?," Energy Economics, Elsevier, vol. 67(C), pages 83-90.
    53. Laurent Ferrara & Clément Marsilli & Juan-Pablo Ortega, 2013. "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?," Working Papers hal-04141198, HAL.
    54. Francesco Ravazzolo & Joaquin Vespignani, 2017. "World steel production: A new monthly indicator of global real economic activity," CAMA Working Papers 2017-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    55. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
    56. Sarun Kamolthip, 2021. "Macroeconomic forecasting with LSTM and mixed frequency time series data," Papers 2109.13777, arXiv.org.
    57. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    58. Michelle T. Armesto & Ruben Hernandez-Murillo & Michael T. Owyang & Jeremy M. Piger, 2007. "Identifying asymmetry in the language of the Beige Book: a mixed data sampling approach," Working Papers 2007-010, Federal Reserve Bank of St. Louis.
    59. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    60. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    61. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
    62. Tingguo Zheng & Xinyue Fan & Wei Jin & Kuangnan Fang, 2024. "Forecasting CPI with multisource data: The value of media and internet information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 702-753, April.
    63. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    64. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    65. Emre Alper, C. & Fendoglu, Salih & Saltoglu, Burak, 2012. "MIDAS volatility forecast performance under market stress: Evidence from emerging stock markets," Economics Letters, Elsevier, vol. 117(2), pages 528-532.
    66. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
    67. Claudia FORONI & Massimiliano MARCELLINO, 2012. "A Comparison of Mixed Frequency Approaches for Modelling Euro Area Macroeconomic Variables," Economics Working Papers ECO2012/07, European University Institute.
    68. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    69. Fokin, Nikita, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
    70. Pan, Zhiyuan & Liu, Li, 2018. "Forecasting stock return volatility: A comparison between the roles of short-term and long-term leverage effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 168-180.
    71. Ba Chu & Shafiullah Qureshi, 2021. "Comparing Out-of-Sample Performance of Machine Learning Methods to Forecast U.S. GDP Growth," Carleton Economic Papers 21-12, Carleton University, Department of Economics.
    72. Hecq, A.W. & Götz, T.B. & Urbain, J.R.Y.J., 2012. "Forecasting Mixed Frequency Time Series with ECM-MIDAS Models," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    73. Virk, Nader & Javed, Farrukh, 2017. "European equity market integration and joint relationship of conditional volatility and correlations," Journal of International Money and Finance, Elsevier, vol. 71(C), pages 53-77.
    74. Michael P. Clements & Ana Beatriz Galvão, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206, November.
    75. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    76. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
    77. Emami Javanmard, M. & Tang, Y. & Wang, Z. & Tontiwachwuthikul, P., 2023. "Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector," Applied Energy, Elsevier, vol. 338(C).
    78. Michael Boldin & Jonathan H. Wright, 2015. "Weather-Adjusting Economic Data," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(2 (Fall)), pages 227-278.
    79. Jonas E. Arias & Minchul Shin, 2020. "Tracking U.S. Real GDP Growth During the Pandemic," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 5(3), pages 9-14, September.
    80. Jung, Alexander, 2017. "Forecasting broad money velocity," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 421-432.
    81. Hong Shen & Qi Pan, 2022. "Risk Contagion between Commodity Markets and the Macro Economy during COVID-19: Evidence from China," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    82. J. Isaac Miller, 2010. "Cointegrating regressions with messy regressors and an application to mixed‐frequency series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 255-277, July.
    83. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    84. Gopal K. Basak & Ravi Jagannathan & Tongshu Ma, 2004. "A Jackknife Estimator for Tracking Error Variance of Optimal Portfolios Constructed Using Estimated Inputs1," NBER Working Papers 10447, National Bureau of Economic Research, Inc.
    85. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    86. Hamilton, James D., 2008. "Daily monetary policy shocks and new home sales," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1171-1190, October.
    87. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    88. Ioannis Chalkiadakis & Gareth W. Peters & Matthew Ames, 2023. "Hybrid ARDL-MIDAS-Transformer time-series regressions for multi-topic crypto market sentiment driven by price and technology factors," Digital Finance, Springer, vol. 5(2), pages 295-365, June.
    89. Yunxu Wang & Chi-Wei Su & Yuchen Zhang & Oana-Ramona Lobonţ & Qin Meng, 2023. "Effectiveness of Principal-Component-Based Mixed-Frequency Error Correction Model in Predicting Gross Domestic Product," Mathematics, MDPI, vol. 11(19), pages 1-14, September.
    90. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    91. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    92. 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.
    93. Zhao, Xin & Han, Meng & Ding, Lili & Kang, Wanglin, 2018. "Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS," Applied Energy, Elsevier, vol. 216(C), pages 132-141.
    94. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    95. Reinhard Ellwanger, Stephen Snudden, 2021. "Predictability of Aggregated Time Series," LCERPA Working Papers bm0127, Laurier Centre for Economic Research and Policy Analysis.
    96. Ghysels, Eric & Miller, J. Isaac, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," CEPR Discussion Papers 9654, C.E.P.R. Discussion Papers.
    97. Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "Constructing a financial fragility index for emerging countries," Finance Research Letters, Elsevier, vol. 11(4), pages 410-419.
    98. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
    99. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201305, University of Hawaii at Manoa, Department of Economics.
    100. Robert M. Kunst & Martin Wagner, 2020. "Economic forecasting: editors’ introduction," Empirical Economics, Springer, vol. 58(1), pages 1-5, January.
    101. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    102. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
    103. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    104. Zhu, Sha & Liu, Qiuhong & Wang, Yan & Wei, Yu & Wei, Guiwu, 2019. "Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    105. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    106. Hanslin Grossmann, Sandra & Scheufele, Rolf, 2015. "Foreign PMIs: A reliable indicator for Swiss exports," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112830, Verein für Socialpolitik / German Economic Association.
    107. Bhadury, Soumya & Ghosh, Saurabh & Kumar, Pankaj, 2019. "Nowcasting GDP Growth Using a Coincident Economic Indicator for India," MPRA Paper 96007, University Library of Munich, Germany.
    108. Valadkhani, Abbas & Smyth, Russell, 2018. "Asymmetric responses in the timing, and magnitude, of changes in Australian monthly petrol prices to daily oil price changes," Energy Economics, Elsevier, vol. 69(C), pages 89-100.
    109. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.
    110. Daniel Hopp, 2022. "Benchmarking Econometric and Machine Learning Methodologies in Nowcasting," Papers 2205.03318, arXiv.org.
    111. Han, Meng & Ding, Lili & Zhao, Xin & Kang, Wanglin, 2019. "Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors," Energy, Elsevier, vol. 171(C), pages 69-76.
    112. Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    113. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    114. Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
    115. Lee, Chien-Chiang & Chen, Mei-Ping & Chang, Chi-Hung, 2014. "Industry co-movement and cross-listing: Do home country factors matter?," Japan and the World Economy, Elsevier, vol. 32(C), pages 96-110.
    116. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
    117. Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
    118. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    119. Guy P. Nason & Ben Powell & Duncan Elliott & Paul A. Smith, 2017. "Should we sample a time series more frequently?: decision support via multirate spectrum estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 353-407, February.
    120. Ye, Wuyi & Jiang, Kunliang & Liu, Xiaoquan, 2021. "Financial contagion and the TIR-MIDAS model," Finance Research Letters, Elsevier, vol. 39(C).
    121. Thomas B. Götz & Alain W. Hecq, 2019. "Granger Causality Testing in Mixed‐Frequency VARs with Possibly (Co)Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 914-935, November.
    122. 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.
    123. Dr. Alain Galli & Dr. Christian Hepenstrick & Dr. Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
    124. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    125. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    126. Hirashima, Ashley & Jones, James & Bonham, Carl S. & Fuleky, Peter, 2017. "Forecasting in a Mixed Up World: Nowcasting Hawaii Tourism," Annals of Tourism Research, Elsevier, vol. 63(C), pages 191-202.
    127. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    128. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    129. Dimpfl, Thomas & Langen, Tobias, 2015. "A Cross-Country Analysis of Unemployment and Bonds with Long-Memory Relations," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112921, Verein für Socialpolitik / German Economic Association.
    130. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    131. Klaus Wohlrabe, 2009. "Macroeconomic forecasting with mixed frequencies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
    132. Julien Chevallier, 2021. "Covid-19 Outbreak and CO2 Emissions: Macro-Financial Linkages," Working Papers 2021-004, Department of Research, Ipag Business School.
    133. Charfeddine, Lanouar & Klein, Tony & Walther, Thomas, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," QBS Working Paper Series 2018/03, Queen's University Belfast, Queen's Business School.
    134. Schreiber, Sven, 2018. "Weather-induced Short-term Fluctuations of Economic Output," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181622, Verein für Socialpolitik / German Economic Association.
    135. Sampi Bravo,James Robert Ezequiel & Jooste,Charl, 2020. "Nowcasting Economic Activity in Times of COVID-19 : An Approximation from the Google Community Mobility Report," Policy Research Working Paper Series 9247, The World Bank.
    136. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
    137. William Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics, revised Feb 2014.
    138. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions, Second Version," PIER Working Paper Archive 08-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Apr 2008.
    139. Ioannis Kasparis & Peter C.B. Phillips, 2009. "Dynamic Misspecification in Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 1700, Cowles Foundation for Research in Economics, Yale University.
    140. Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2023. "Nowcasting consumer price inflation using high-frequency scanner data: Evidence from Germany," Discussion Papers 34/2023, Deutsche Bundesbank.
    141. Proietti, Tommaso & Giovannelli, Alessandro & Ricchi, Ottavio & Citton, Ambra & Tegami, Christían & Tinti, Cristina, 2021. "Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1376-1398.
    142. MAMATZAKIS, emmanuel & MAMATZAKIS, E, 2022. "Understanding the impact of travel on wellbeing: evidence for Great Britain during the pandemic," MPRA Paper 112974, University Library of Munich, Germany.
    143. Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
    144. Lynda Khalaf & Maral Kichian & Charles Saunders & Marcel Voia, 2021. "Dynamic panels with MIDAS covariates: Nonlinearity, estimation and fit," Post-Print hal-03528880, HAL.
    145. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
    146. Philip Hans Franses & Eva Janssens, 2017. "Recovering Historical Inflation Data from Postage Stamps Prices," JRFM, MDPI, vol. 10(4), pages 1-11, November.
    147. Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.
    148. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    149. Clements, Michael P. & Galvao, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US output growth and inflation," Economic Research Papers 269743, University of Warwick - Department of Economics.
    150. Pan, Zhiyuan & Wang, Qing & Wang, Yudong & Yang, Li, 2018. "Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model," Energy Economics, Elsevier, vol. 72(C), pages 177-187.
    151. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    152. Luke Mosley & Idris A. Eckley & Alex Gibberd, 2022. "Sparse temporal disaggregation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2203-2233, October.
    153. Pradeep Mishra & Khder Alakkari & Mostafa Abotaleb & Pankaj Kumar Singh & Shilpi Singh & Monika Ray & Soumitra Sankar Das & Umme Habibah Rahman & Ali J. Othman & Nazirya Alexandrovna Ibragimova & Gulf, 2021. "Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)," Data, MDPI, vol. 6(11), pages 1-15, November.
    154. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Cholesky-MIDAS model for predicting stock portfolio volatility," Centre for Growth and Business Cycle Research Discussion Paper Series 149, Economics, The University of Manchester.
    155. Xu Gong & Mingchao Wang & Liuguo Shao, 2022. "The impact of macro economy on the oil price volatility from the perspective of mixing frequency," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4487-4514, October.
    156. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    157. Marozzi, Armando, 2021. "The ECB's tracker: nowcasting the press conferences of the ECB," Working Paper Series 2609, European Central Bank.
    158. Diakonova, Marina & Ghirelli, Corinna & Molina, Luis & Pérez, Javier J., 2023. "The economic impact of conflict-related and policy uncertainty shocks: The case of Russia," International Economics, Elsevier, vol. 174(C), pages 69-90.
    159. Götz, Thomas B. & Hecq, Alain & Smeekes, Stephan, 2015. "Testing for Granger causality in large mixed-frequency VARs," Discussion Papers 45/2015, Deutsche Bundesbank.
    160. He, Yongda & Lin, Boqiang, 2018. "Forecasting China's total energy demand and its structure using ADL-MIDAS model," Energy, Elsevier, vol. 151(C), pages 420-429.
    161. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    162. Guerrero Víctor M. & García Andrea C. & Sainz Esperanza, 2013. "Rapid Estimates of Mexico’s Quarterly GDP," Journal of Official Statistics, Sciendo, vol. 29(3), pages 397-423, June.
    163. Akbar Marvasti & Sami Dakhlia, 2021. "Minimum information management and price‐abundance relationships in a fishery," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(4), pages 491-518, December.
    164. Chaudhuri, Malika & Calantone, Roger J. & Voorhees, Clay M. & Cockrell, Seth, 2018. "Disentangling the effects of promotion mix on new product sales: An examination of disaggregated drivers and the moderating effect of product class," Journal of Business Research, Elsevier, vol. 90(C), pages 286-294.
    165. Jianhao Lin & Jiacheng Fan & Yifan Zhang & Liangyuan Chen, 2023. "Real‐time macroeconomic projection using narrative central bank communication," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 202-221, March.
    166. Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021. "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Sciendo, vol. 16(2), pages 43-52, December.
    167. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    168. Andrii Babii, 2020. "High-dimensional mixed-frequency IV regression," Papers 2003.13478, arXiv.org.
    169. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    170. Michal Franta & David Havrlant & Marek Rusnak, 2014. "Forecasting Czech GDP Using Mixed-Frequency Data Models," Working Papers 2014/08, Czech National Bank.
    171. Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
    172. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
    173. 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.
    174. Rong Fu & Luze Xie & Tao Liu & Juan Huang & Binbin Zheng, 2022. "Chinese Economic Growth Projections Based on Mixed Data of Carbon Emissions under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    175. Smith Paul, 2016. "Nowcasting UK GDP during the depression," Working Papers 1606, University of Strathclyde Business School, Department of Economics.
    176. Deschamps, Bruno & Ioannidis, Christos & Ka, Kook, 2020. "High-frequency credit spread information and macroeconomic forecast revision," International Journal of Forecasting, Elsevier, vol. 36(2), pages 358-372.
    177. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    178. Valentina Aprigliano & Guerino Ardizzi & Alessia Cassetta & Alessandro Cavallero & Simone Emiliozzi & Alessandro Gambini & Nazzareno Renzi & Roberta Zizza, 2021. "Exploiting payments to track Italian economic activity: the experience at Banca d’Italia," Questioni di Economia e Finanza (Occasional Papers) 609, Bank of Italy, Economic Research and International Relations Area.
    179. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Post-Print halshs-04344131, HAL.
    180. Chaoyi Chen & Yiguo Sun & Yao Rao, 2023. "Threshold MIDAS Forecasting of Inflation Rate," Working Papers 202314, University of Liverpool, Department of Economics.
    181. Wink Junior, Marcos Vinício & Pereira, Pedro Luiz Valls, 2011. "Modeling and Forecasting of Realized Volatility: Evidence from Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(2), December.
    182. Emilian DOBRESCU, 2020. "Self-fulfillment degree of economic expectations within an integrated space: The European Union case study," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-32, December.
    183. Dario Buono & George Kapetanios & Massimiliano Marcellino & Gianluigi Mazzi & Fotis Papailias, 2018. "Big Data Econometrics: Now Casting and Early Estimates," BAFFI CAREFIN Working Papers 1882, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    184. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    185. Chunpeng Yang & Rengui Zhang, 2014. "Does mixed-frequency investor sentiment impact stock returns? Based on the empirical study of MIDAS regression model," Applied Economics, Taylor & Francis Journals, vol. 46(9), pages 966-972, March.
    186. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
    187. d’Aspremont, Alexandre & Arous, Simon Ben & Bricongne, Jean-Charles & Lietti, Benjamin & Meunier, Baptiste, 2024. "Satellites turn “concrete”: tracking cement with satellite data and neural networks," Working Paper Series 2900, European Central Bank.
    188. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    189. Edward S. Knotek & Saeed Zaman, 2017. "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 931-968, August.
    190. Zhang, Jin & Li, Pujiang & Zhao, Guochang, 2018. "Is power generation really the gold measure of the Chinese economy? A conceptual and empirical assessment," Energy Policy, Elsevier, vol. 121(C), pages 211-216.
    191. Frömmel, Michael & Midiliç, Murat, 2021. "Daily currency interventions in an emerging market: Incorporating reserve accumulation to the reaction function," Economic Modelling, Elsevier, vol. 97(C), pages 461-476.
    192. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    193. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    194. Wang, Xinyu & Qi, Zikang & Huang, Jianglu, 2023. "How do monetary shock, financial crisis, and quotation reform affect the long memory of exchange rate volatility? Evidence from major currencies," Economic Modelling, Elsevier, vol. 120(C).
    195. Sihong Chen & Qi Li & Qiaoyu Wang & Yu Yvette Zhang, 2023. "Multivariate models of commodity futures markets: a dynamic copula approach," Empirical Economics, Springer, vol. 64(6), pages 3037-3057, June.
    196. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methods of the Ifo short-term forecast," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    197. Naif Alsagr & Stefan F. Van Hemmen Almazor, 2020. "Oil Rent, Geopolitical Risk and Banking Sector Performance," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 305-314.
    198. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    199. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
    200. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.
    201. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
    202. Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
    203. Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Carlos D. Rojas-Martínez, 2021. "Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches," Borradores de Economia 1168, Banco de la Republica de Colombia.
    204. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    205. Alain Hecq & Marie Ternes & Ines Wilms, 2021. "Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions," Papers 2102.11780, arXiv.org, revised Mar 2022.
    206. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    207. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    208. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    209. Turhan, Ibrahim M. & Sensoy, Ahmet & Hacihasanoglu, Erk, 2015. "Shaping the manufacturing industry performance: MIDAS approach," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 286-290.
    210. Feng-Li Lin & Mei-Chih Wang, 2019. "Does economic growth cause military expenditure to go up? Using MF-VAR model," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(6), pages 3097-3117, November.
    211. Maria Begicheva & Alexey Zaytsev, 2021. "Bank transactions embeddings help to uncover current macroeconomics," Papers 2110.12000, arXiv.org, revised Dec 2021.
    212. Peng-Fei Dai & Xiong Xiong & Wei-Xing Zhou, 2020. "The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model," Papers 2007.12838, arXiv.org.
    213. Bahar Şen Doğan & Murat Midiliç, 2019. "Forecasting Turkish real GDP growth in a data-rich environment," Empirical Economics, Springer, vol. 56(1), pages 367-395, January.
    214. Michael P. Clements & David F. Hendry, 2005. "Guest Editors’ Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
    215. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2013. "Testing for Granger Causality with Mixed Frequency Data," CEPR Discussion Papers 9655, C.E.P.R. Discussion Papers.
    216. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
    217. Murat Körs & Mehmet Baha Karan, 2023. "Stock exchange volatility forecasting under market stress with MIDAS regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 295-306, January.
    218. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon, 2014. "Real-Time Nowcasting of Nominal GDP Under Structural Breaks," Staff Working Papers 14-39, Bank of Canada.
    219. Cláudia Duarte, 2014. "Autoregressive augmentation of MIDAS regressions," Working Papers w201401, Banco de Portugal, Economics and Research Department.
    220. Jian Chai & Puju Cao & Xiaoyang Zhou & Kin Keung Lai & Xiaofeng Chen & Siping (Sue) Su, 2018. "The Conductive and Predictive Effect of Oil Price Fluctuations on China’s Industry Development Based on Mixed-Frequency Data," Energies, MDPI, vol. 11(6), pages 1-14, May.
    221. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 55.
    222. Freitag L., 2014. "Default probabilities, CDS premiums and downgrades : A probit-MIDAS analysis," Research Memorandum 038, Maastricht University, Graduate School of Business and Economics (GSBE).
    223. James D. Hamilton, 2008. "Daily Monetary Policy Shocks and the Delayed Response of New Home Sales," NBER Working Papers 14223, National Bureau of Economic Research, Inc.
    224. Anthony S. Tay, 2007. "Financial Variables as Predictors of Real Output Growth," Development Economics Working Papers 22482, East Asian Bureau of Economic Research.
    225. Bhaghoe, Sailesh & Ooft, Gavin, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
    226. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.
    227. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    228. Alejandro Fernández Cerezo, 2023. "A supply-side GDP nowcasting model," Economic Bulletin, Banco de España, issue 2023/Q1.
    229. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    230. Valentina Aprigliano & Guerino Ardizzi & Libero Monteforte, 2017. "Using the payment system data to forecast the Italian GDP," Temi di discussione (Economic working papers) 1098, Bank of Italy, Economic Research and International Relations Area.
    231. Alper, C. Emre & Fendoglu, Salih & Saltoglu, Burak, 2008. "Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets," MPRA Paper 7460, University Library of Munich, Germany.
    232. Gao, Bin & Yang, Chunpeng, 2017. "Forecasting stock index futures returns with mixed-frequency sentiment," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 69-83.
    233. Boriss Siliverstovs, 2015. "Dissecting the purchasing managers' index," KOF Working papers 15-376, KOF Swiss Economic Institute, ETH Zurich.
    234. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
    235. Miller, J. Isaac & Nam, Kyungsik, 2022. "Modeling peak electricity demand: A semiparametric approach using weather-driven cross-temperature response functions," Energy Economics, Elsevier, vol. 114(C).
    236. Simona Boffelli & Vasiliki D. Skintzi & Giovanni Urga, 2017. "High- and Low-Frequency Correlations in European Government Bond Spreads and Their Macroeconomic Drivers," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 62-105.
    237. J. Isaac Miller, 2014. "Simple Robust Tests for the Specification of High-Frequency Predictors of a Low-Frequency Series," Working Papers 1412, Department of Economics, University of Missouri.
    238. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2016. "Real-time nowcasting of nominal GDP with structural breaks," Journal of Econometrics, Elsevier, vol. 191(2), pages 312-324.
    239. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    240. Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
    241. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    242. Thomas Walther & Tony Klein, 2018. "Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting," Working Papers on Finance 1815, University of St. Gallen, School of Finance.
    243. Mahmut Gunay, 2018. "Nowcasting Annual Turkish GDP Growth with MIDAS," CBT Research Notes in Economics 1810, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    244. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    245. Modugno, Michele, 2011. "Nowcasting inflation using high frequency data," Working Paper Series 1324, European Central Bank.
    246. Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
    247. Götz, Thomas B. & Hauzenberger, Klemens, 2018. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers 40/2018, Deutsche Bundesbank.
    248. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    249. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
    250. Lourenço, Nuno & Rua, António, 2021. "The Daily Economic Indicator: tracking economic activity daily during the lockdown," Economic Modelling, Elsevier, vol. 100(C).
    251. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
    252. Gong, Xu & Sun, Yi & Du, Zhili, 2022. "Geopolitical risk and China's oil security," Energy Policy, Elsevier, vol. 163(C).
    253. Michelle T. Armesto & Kristie M. Engemann & Michael T. Owyang, 2010. "Forecasting with mixed frequencies," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 521-536.
    254. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org.
    255. Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024. "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers) 1446, Bank of Italy, Economic Research and International Relations Area.
    256. Sara Boni & Massimiliano Caporin & Francesco Ravazzolo, 2024. "Nowcasting Inflation at Quantiles: Causality from Commodities," BEMPS - Bozen Economics & Management Paper Series BEMPS102, Faculty of Economics and Management at the Free University of Bozen.
    257. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    258. Stefan Neuwirth, 2017. "Time-varying mixed frequency forecasting: A real-time experiment," KOF Working papers 17-430, KOF Swiss Economic Institute, ETH Zurich.
    259. Tretyakov, Dmitriy & Fokin, Nikita, 2020. "Помогают Ли Высокочастотные Данные В Прогнозировании Российской Инфляции? [Does the high-frequency data is helpful for forecasting Russian inflation?]," MPRA Paper 109556, University Library of Munich, Germany.
    260. Götz, Thomas B. & Hecq, Alain & Urbain, Jean-Pierre, 2016. "Combining forecasts from successive data vintages: An application to U.S. growth," International Journal of Forecasting, Elsevier, vol. 32(1), pages 61-74.
    261. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    262. Emmanuel Apergis & Nicholas Apergis, 2021. "Can the COVID-19 Pandemic and Oil Prices Drive the US Partisan Conflict Index," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 1(1), pages 1-4.
    263. Yun Liu & Yeonwoo Rho, 2018. "On the Choice of Instruments in Mixed Frequency Specification Tests," Papers 1809.05503, arXiv.org.
    264. Emmanuel Mamatzakis & Mike G. Tsionas & Steven Ongena, 2023. "Why do households repay their debt in UK during the COVID-19 crisis?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(8), pages 1789-1823, April.
    265. Hagher Ben Rhomdhane & Brahim Mehdi Benlallouna, 2022. "Nowcasting real GDP in Tunisia using large datasets and mixed-frequency models," IHEID Working Papers 02-2022, Economics Section, The Graduate Institute of International Studies.
    266. Guy P. Nason & James L. Wei, 2022. "Quantifying the economic response to COVID‐19 mitigations and death rates via forecasting purchasing managers' indices using generalised network autoregressive models with exogenous variables," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1778-1792, October.
    267. Julián Alonso Cárdenas-Cárdenas & Edgar Caicedo-García & Eliana R. González Molano, 2020. "Estimación de la variación del precio de los alimentos con modelos de frecuencias mixtas," Borradores de Economia 1109, Banco de la Republica de Colombia.
    268. Xiaqing Su & Zhe Liu, 2021. "Sector Volatility Spillover and Economic Policy Uncertainty: Evidence from China’s Stock Market," Mathematics, MDPI, vol. 9(12), pages 1-22, June.
    269. Gong, Yuting & Chen, Qiang & Liang, Jufang, 2018. "A mixed data sampling copula model for the return-liquidity dependence in stock index futures markets," Economic Modelling, Elsevier, vol. 68(C), pages 586-598.
    270. Dr. Sandra Hanslin Grossmann & Dr. Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.
    271. Motegi, Kaiji & Sadahiro, Akira, 2018. "Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 118-128.
    272. Zhang Wu & Terence Tai-Leung Chong, 2021. "Does the macroeconomy matter to market volatility? Evidence from US industries," Empirical Economics, Springer, vol. 61(6), pages 2931-2962, December.
    273. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
    274. Marie Bessec, 2015. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Post-Print hal-01276824, HAL.
    275. Jeffrey C. Chen & Abe Dunn & Kyle Hood & Alexander Driessen & Andrea Batch, 2019. "Off to the Races: A Comparison of Machine Learning and Alternative Data for Predicting Economic Indicators," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 373-402, National Bureau of Economic Research, Inc.
    276. 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).
    277. Samuel N. Cohen & Silvia Lui & Will Malpass & Giulia Mantoan & Lars Nesheim & 'Aureo de Paula & Andrew Reeves & Craig Scott & Emma Small & Lingyi Yang, 2023. "Nowcasting with signature methods," Papers 2305.10256, arXiv.org.
    278. Ding, Lili & Zhao, Zhongchao & Wang, Lei, 2022. "Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?," Applied Energy, Elsevier, vol. 312(C).
    279. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2023. "S&P 500 volatility, volatility regimes, and economic uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1362-1387, October.
    280. Denisa BANULESCU-RADU & Laurent FERRARA & Clément MARSILLI, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," LEO Working Papers / DR LEO 2710, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    281. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    282. Conefrey, Thomas & Walsh, Graeme, 2018. "A Monthly Indicator of Economic Activity for Ireland," Economic Letters 14/EL/18, Central Bank of Ireland.
    283. Matěj Liberda, 2017. "Mixed-frequency Drivers of Precious Metal Prices," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(6), pages 2007-2015.
    284. Byron Botha & Geordie Reid & Tim Olds & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African GDP using a suite of statistical models," Working Papers 11001, South African Reserve Bank.
    285. Poncela, Pilar & Guerrero, Víctor & Islas C., Alejandro & Rodríguez, Julio & Sánchez-Mangas, Rocío, 2014. "Mexico: Combining monthly inflation predictions from surveys," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    286. Wang, Ruina & Li, Jinfang, 2021. "The influence and predictive powers of mixed-frequency individual stock sentiment on stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    287. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
    288. Laine, Olli-Matti & Lindblad, Annika, 2020. "Nowcasting Finnish GDP growth using financial variables: a MIDAS approach," BoF Economics Review 4/2020, Bank of Finland.
    289. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    290. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    291. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.
    292. Roberto Steri, 2015. "Collateral-Based Asset Pricing," 2015 Meeting Papers 293, Society for Economic Dynamics.
    293. Uğurlu-Yıldırım, Ecenur & Şendeniz-Yüncü, İlkay, 2021. "Additional factor in asset-pricing: Institutional ownership," Finance Research Letters, Elsevier, vol. 40(C).
    294. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
    295. Angelos Kanas & Panagiotis D. Zervopoulos, 2020. "Systemic risk-shifting in U.S. commercial banking," Review of Quantitative Finance and Accounting, Springer, vol. 54(2), pages 517-539, February.
    296. Stefan Gebauer, 2017. "The Use of Financial Market Variables in Forecasting," DIW Roundup: Politik im Fokus 115, DIW Berlin, German Institute for Economic Research.
    297. Michael D. Boldin & Jonathan H. Wright, 2015. "Weather-adjusting employment data," Working Papers 15-5, Federal Reserve Bank of Philadelphia.
    298. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
    299. Thomas Walther & Lanouar Charfeddine & Tony Klein, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," Working Papers on Finance 1816, University of St. Gallen, School of Finance.
    300. Dirk Drechsel & Stefan Neuwirth, 2016. "Taming volatile high frequency data with long lag structure: An optimal filtering approach for forecasting," KOF Working papers 16-407, KOF Swiss Economic Institute, ETH Zurich.
    301. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    302. Luke Mosley & Idris Eckley & Alex Gibberd, 2021. "Sparse Temporal Disaggregation," Papers 2108.05783, arXiv.org, revised Oct 2022.
    303. Franses, Ph.H.B.F., 2016. "Yet another look at MIDAS regression," Econometric Institute Research Papers EI2016-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    304. Marc Francke & Alex Van De Minne, 2022. "Daily appraisal of commercial real estate a new mixed frequency approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(5), pages 1257-1281, September.
    305. Ruey Yau & C. James Hueng, 2019. "Nowcasting GDP Growth for Small Open Economies with a Mixed-Frequency Structural Model," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 177-198, June.
    306. Chi-Wei Su & Yuru Song & Hsu-Ling Chang & Weike Zhang & Meng Qin, 2023. "Could Cryptocurrency Policy Uncertainty Facilitate U.S. Carbon Neutrality?," Sustainability, MDPI, vol. 15(9), pages 1-15, May.
    307. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
    308. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.
    309. Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    310. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
    311. Yun-Yeong Kim, 2016. "Dynamic Analyses Using VAR Model with Mixed Frequency Data through Observable Representation," Korean Economic Review, Korean Economic Association, vol. 32, pages 41-75.
    312. Liu, Min & Lee, Chien-Chiang, 2022. "Is gold a long-run hedge, diversifier, or safe haven for oil? Empirical evidence based on DCC-MIDAS," Resources Policy, Elsevier, vol. 76(C).
    313. Selma Toker & Nimet Özbay & Kristofer Månsson, 2022. "Mixed data sampling regression: Parameter selection of smoothed least squares estimator," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 718-751, July.
    314. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
    315. Byron Botha & Tim Olds & Geordie Reid & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African gross domestic product using a suite of statistical models," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 526-554, December.

  12. Hsu, Jason C. & Saa-Requejo, Jesus & Santa-Clara, Pedro, 2003. "Bond Pricing with Default Risk," University of California at Los Angeles, Anderson Graduate School of Management qt5bb1j39q, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Jan Ericsson & Joel Reneby, 1998. "A framework for valuing corporate securities," Applied Mathematical Finance, Taylor & Francis Journals, vol. 5(3-4), pages 143-163.
    2. Zvika Afik & Ohad Arad & Koresh Galil, 2012. "Using Merton model: an empirical assessment of alternatives," Working Papers 1202, Ben-Gurion University of the Negev, Department of Economics.
    3. Han-Hsing Lee & Ren-Raw Chen & Cheng Few Lee, 2020. "Empirical Studies of Structural Credit Risk Models and the Application in Default Prediction: Review and New Evidence," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 50, pages 1845-1901, World Scientific Publishing Co. Pte. Ltd..
    4. Fabian Astic & Agnès Tourin, 2014. "On The Credit Risk Of Secured Loans With Maximum Loan-To-Value Covenants," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(08), pages 1-19.
    5. Martina Nardon, 2005. "Valuing defaultable bonds: an excursion time approach," Finance 0511015, University Library of Munich, Germany.
    6. Ericsson, Jan & Reneby, Joel, 2003. "Valuing Corporate Liabilities," SIFR Research Report Series 15, Institute for Financial Research.
    7. Hugues Pirotte, 1999. "Implementing a Structural Valuation Model of Swap Credit-Sensitive Rates," Working Papers CEB 99-001.RS, ULB -- Universite Libre de Bruxelles.
    8. Robert Elliott & Jia Shen, 2015. "Dynamic optimal capital structure with regime switching," Annals of Finance, Springer, vol. 11(2), pages 199-220, May.
    9. Vilimir Yordanov, 2012. "The Bulgarian Foreign and Domestic Debt ??? A No-Arbitrage Macrofinancial View," William Davidson Institute Working Papers Series wp1032, William Davidson Institute at the University of Michigan.
    10. Gregor Dorfleitner & Paul Schneider & Tanja Veža, 2011. "Flexing the default barrier," Quantitative Finance, Taylor & Francis Journals, vol. 11(12), pages 1729-1743.
    11. Delianedis, Gordon & Geske, Robert, 2001. "The Components of Corporate Credit Spreads: Default, Recovery, Tax, Jumps, Liquidity, and Market Factors," University of California at Los Angeles, Anderson Graduate School of Management qt32x284q3, Anderson Graduate School of Management, UCLA.
    12. Mr. Marcel Peter & Martín Grandes, 2005. "How Important Is Sovereign Risk in Determining Corporate Default Premia? The Case of South Africa," IMF Working Papers 2005/217, International Monetary Fund.
    13. Kanak Patel & Prodromos Vlamis, 2006. "An Empirical Estimation of Default Risk of the UK Real Estate Companies," The Journal of Real Estate Finance and Economics, Springer, vol. 32(1), pages 21-40, February.
    14. Reneby, Joel & Ericsson, Jan, 2001. "The Valuation of Corporate Liabilities: Theory and Tests," SSE/EFI Working Paper Series in Economics and Finance 445, Stockholm School of Economics, revised 07 Jan 2003.
    15. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.

  13. John H. Cochrane & Francis A. Longstaff & Pedro Santa-Clara, 2003. "Two Trees: Asset Price Dynamics Induced by Market Clearing," NBER Working Papers 10116, National Bureau of Economic Research, Inc.

    Cited by:

    1. Theodoros Diasakos, 2008. "Comparative Statics of Asset Prices," Carlo Alberto Notebooks 72, Collegio Carlo Alberto, revised 2011.
    2. Frieder, Laura, 2008. "Investor and price response to patterns in earnings surprises," Journal of Financial Markets, Elsevier, vol. 11(3), pages 259-283, August.
    3. Francis A. Longstaff, 2004. "Financial Claustrophobia: Asset Pricing in Illiquid Markets," NBER Working Papers 10411, National Bureau of Economic Research, Inc.
    4. Johnson, Timothy C., 2006. "Dynamic liquidity in endowment economies," Journal of Financial Economics, Elsevier, vol. 80(3), pages 531-562, June.

  14. Ledoit, Olivier & Santa-Clara, Pedro & Yan, Shu, 2002. "Relative Pricing of Options with Stochastic Volatility," University of California at Los Angeles, Anderson Graduate School of Management qt7jp8f42t, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Aït-Sahalia, Yacine & Amengual, Dante & Manresa, Elena, 2015. "Market-based estimation of stochastic volatility models," Journal of Econometrics, Elsevier, vol. 187(2), pages 418-435.
    2. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    3. Alexey MEDVEDEV & Olivier SCAILLET, 2004. "A Simple Calibration Procedure of Stochastic Volatility Models with Jumps by Short Term Asymptotics," FAME Research Paper Series rp93, International Center for Financial Asset Management and Engineering.
    4. Carol Alexander & Leonardo Nogueira, 2004. "Stochastic Local Volatility," ICMA Centre Discussion Papers in Finance icma-dp2008-02, Henley Business School, University of Reading, revised Mar 2008.
    5. Sebastian Herrmann & Johannes Muhle-Karbe, 2017. "Model uncertainty, recalibration, and the emergence of delta–vega hedging," Finance and Stochastics, Springer, vol. 21(4), pages 873-930, October.
    6. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    7. Ai[diaeresis]t-Sahalia, Yacine & Kimmel, Robert, 2007. "Maximum likelihood estimation of stochastic volatility models," Journal of Financial Economics, Elsevier, vol. 83(2), pages 413-452, February.
    8. Martin Schweizer & Johannes Wissel, 2008. "Term Structures Of Implied Volatilities: Absence Of Arbitrage And Existence Results," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 77-114, January.
    9. Yuhyeon Bak & Cheolbeom Park, 2020. "Exchange Rate Predictability, Risk Premiums, and Predictive System," Discussion Paper Series 2006, Institute of Economic Research, Korea University.
    10. Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.
    11. Carey, Alexander, 2008. "Natural volatility and option pricing," MPRA Paper 6709, University Library of Munich, Germany.
    12. Carol Alexander & Leonardo M. Nogueira, 2004. "Hedging with Stochastic and Local Volatility," ICMA Centre Discussion Papers in Finance icma-dp2004-10, Henley Business School, University of Reading, revised Dec 2004.
    13. Itkin, Andrey, 2015. "To sigmoid-based functional description of the volatility smile," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 264-291.
    14. Sebastian Herrmann & Johannes Muhle-Karbe, 2017. "Model Uncertainty, Recalibration, and the Emergence of Delta-Vega Hedging," Papers 1704.04524, arXiv.org.
    15. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2008. "High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence," NBER Working Papers 13739, National Bureau of Economic Research, Inc.
    16. Martin Schweizer & Johannes Wissel, 2008. "Arbitrage-free market models for option prices: the multi-strike case," Finance and Stochastics, Springer, vol. 12(4), pages 469-505, October.
    17. Bas Peeters, 2012. "Risk premiums in a simple market model for implied volatility," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 739-748, January.
    18. Moriggia, V. & Muzzioli, S. & Torricelli, C., 2009. "On the no-arbitrage condition in option implied trees," European Journal of Operational Research, Elsevier, vol. 193(1), pages 212-221, February.
    19. Yacine Ait-Sahalia & Robert Kimmel, 2004. "Maximum Likelihood Estimation of Stochastic Volatility Models," NBER Working Papers 10579, National Bureau of Economic Research, Inc.

  15. Michael W. Brandt & Pedro Santa-Clara, 2001. "Simulated Likelihood Estimation of Diffusions with an Application to Exchange Rate Dynamics in Incomplete Markets," NBER Technical Working Papers 0274, National Bureau of Economic Research, Inc.

    Cited by:

    1. Ruijun Bu & Fredj Jawadi & Yuyi Li, 2020. "A multifactor transformed diffusion model with applications to VIX and VIX futures," Econometric Reviews, Taylor & Francis Journals, vol. 39(1), pages 27-53, January.
    2. Hans Dewachter & Kristien Smedts, 2007. "Limits to international arbitrage: an empirical evaluation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(3), pages 273-285.
    3. Isambi Mbalawata & Simo Särkkä & Heikki Haario, 2013. "Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering," Computational Statistics, Springer, vol. 28(3), pages 1195-1223, June.
    4. Taboga, Marco & Pericoli, Marcello, 2008. "Bond risk premia, macroeconomic fundamentals and the exchange rate," MPRA Paper 9523, University Library of Munich, Germany.
    5. Yun, Jaeho, 2014. "Out-of-sample density forecasts with affine jump diffusion models," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 74-87.
    6. Peter C. B. Phillips & Jun Yu, 2006. "A Two-Stage Realized Volatility Approach to Estimation of Diffusion Processes with Discrete," Macroeconomics Working Papers 22472, East Asian Bureau of Economic Research.
    7. Qiang Dai & Kenneth Singleton, 2003. "Term Structure Dynamics in Theory and Reality," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 631-678, July.
    8. Robert J. Hodrick & Tuomas Tomunen, 2018. "Taking the Cochrane-Piazzesi Term Structure Model Out of Sample: More Data, Additional Currencies, and FX Implications," NBER Working Papers 25092, National Bureau of Economic Research, Inc.
    9. S. Bordignon & D. Raggi, 2008. "Volatility, Jumps and Predictability of Returns: a Sequential Analysis," Working Papers 636, Dipartimento Scienze Economiche, Universita' di Bologna.
    10. Eric Ghysels & Jean-Pierre Florens & Mikhail Chernov & Marine Carrasco, 2003. "Efficient Estimation of Jump Diffusions and General Dynamic Models with a Continuum of Moment Conditions," CIRANO Working Papers 2003s-02, CIRANO.
    11. A. S. Hurn & K. A. Lindsay & A. J. McClelland, 2015. "Estimating the Parameters of Stochastic Volatility Models Using Option Price Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 579-594, October.
    12. Chernov, Mikhail & Creal, Drew, 2022. "International yield curves and currency puzzles," CEPR Discussion Papers 13252, C.E.P.R. Discussion Papers.
    13. Nikola Mirkov, 2014. "International financial transmission of the Fed's monetary policy," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(2), pages 7-49, September.
    14. A. Hurn & J. Jeisman & K. Lindsay, 2007. "Teaching an Old Dog New Tricks: Improved Estimation of the Parameters of Stochastic Differential Equations by Numerical Solution of the Fokker-Planck Equation," NCER Working Paper Series 9, National Centre for Econometric Research.
    15. Gudmundsson, Hilmar & Vyncke, David, 2019. "On the calibration of the 3/2 model," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1178-1192.
    16. Brandt, Michael & Cochrane, John & Santa-Clara, Pedro, 2001. "International Risk Sharing is Better Than You Think (or Exchange Rates are Much Too Smooth!," University of California at Los Angeles, Anderson Graduate School of Management qt1jw137zd, Anderson Graduate School of Management, UCLA.
    17. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    18. Orazio Di Miscia, 2005. "Term structure of interest models: concept and estimation problem in a continuous-time setting," Finance 0504017, University Library of Munich, Germany.
    19. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modeling Multivariate Interest Rates using Time-Varying Copulas and Reducible Stochastic Differential Equations," Working Papers halshs-00408014, HAL.
    20. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2010. "Properties of Foreign Exchange Risk Premia," MPRA Paper 21302, University Library of Munich, Germany.
    21. Bakshi, Gurdip & Carr, Peter & Wu, Liuren, 2008. "Stochastic risk premiums, stochastic skewness in currency options, and stochastic discount factors in international economies," Journal of Financial Economics, Elsevier, vol. 87(1), pages 132-156, January.
    22. Mirkov, Nikola, 2012. "International Financial Transmission of the US Monetary Policy: An Empirical Assessment," Working Papers on Finance 1201, University of St. Gallen, School of Finance.
    23. Christopher S. Jones, 2003. "Nonlinear Mean Reversion in the Short-Term Interest Rate," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 793-843, July.
    24. Aït-Sahalia, Yacine & Kimmel, Robert L., 2010. "Estimating affine multifactor term structure models using closed-form likelihood expansions," Journal of Financial Economics, Elsevier, vol. 98(1), pages 113-144, October.
    25. Xiaodong Du & Cindy L. Yu & Dermot J. Hayes, 2009. "Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets: A Bayesian Analysis," Center for Agricultural and Rural Development (CARD) Publications 09-wp491, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    26. Xiaodong Du & Dermot J. Hayes & Cindy L. Yu, 2009. "Dynamics of Biofuel Stock Prices: A Bayesian Approach," Center for Agricultural and Rural Development (CARD) Publications 09-wp498, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    27. Phillips, Peter C.B. & Yu, Jun, 2009. "A two-stage realized volatility approach to estimation of diffusion processes with discrete data," Journal of Econometrics, Elsevier, vol. 150(2), pages 139-150, June.
    28. M. Hadzi-Vaskov & C.J.M. Kool, 2007. "Stochastic Discount Factor Approach to International Risk-Sharing: Evidence from Fixed Exchange Rate Episodes," Working Papers 07-33, Utrecht School of Economics.
    29. Pan, Jun, 2002. "The jump-risk premia implicit in options: evidence from an integrated time-series study," Journal of Financial Economics, Elsevier, vol. 63(1), pages 3-50, January.
    30. R. Anton Braun & Huiyu Li & John Stachurski, 2011. "Generalized Look-Ahead Methods for Computing Stationary Densities," ANU Working Papers in Economics and Econometrics 2011-558, Australian National University, College of Business and Economics, School of Economics.
    31. Xibin Zhang & Robert D. Brooks & Maxwell L. King, 2007. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics.
    32. Jeremy Graveline & Irina Zviadadze & Mikhail Chernov, 2012. "Crash Risk in Currency Returns," 2012 Meeting Papers 753, Society for Economic Dynamics.
    33. Dennis Kristensen & Young Jun Lee & Antonio Mele, 2023. "Closed-form approximations of moments and densities of continuous-time Markov models," Papers 2308.09009, arXiv.org.
    34. Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CARF F-Series CARF-F-181, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    35. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    36. Federico M. Bandi & Peter C.B. Phillips, 2005. "A Simple Approach to the Parametric Estimation of Potentially Nonstationary Diffusions," Cowles Foundation Discussion Papers 1522, Cowles Foundation for Research in Economics, Yale University.
    37. Bakshi, Gurdip & Ju, Nengjiu & Ou-Yang, Hui, 2006. "Estimation of continuous-time models with an application to equity volatility dynamics," Journal of Financial Economics, Elsevier, vol. 82(1), pages 227-249, October.
    38. Veiga, Helena, 2006. "Are feedback factors important in modelling financial data?," DES - Working Papers. Statistics and Econometrics. WS ws060101, Universidad Carlos III de Madrid. Departamento de Estadística.
    39. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2011. "Properties of Foreign Exchange Risk Premiums," CEPR Discussion Papers 8503, C.E.P.R. Discussion Papers.
    40. Choi, Hwan-sik, 2016. "Information theory for maximum likelihood estimation of diffusion models," Journal of Econometrics, Elsevier, vol. 191(1), pages 110-128.
    41. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    42. Metodij Hadzi-Vaskov & Clemens J.M. Kool, 2007. "Stochastic Discount Factor Approach to International Risk-Sharing: A Trilateral Framework," EcoMod2007 23900031, EcoMod.
    43. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
    44. Shu Wu, 2007. "Interest Rate Risk and the Forward Premium Anomaly in Foreign Exchange Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2-3), pages 423-442, March.
    45. Michael Rockinger & Maria Semenova, 2005. "Estimation of Jump-Diffusion Process vis Empirical Characteristic Function," FAME Research Paper Series rp150, International Center for Financial Asset Management and Engineering.
    46. Peter C. B. Phillips & Jun Yu, 2009. "Simulation-Based Estimation of Contingent-Claims Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3669-3705, September.
    47. Song, Zhaogang, 2011. "A martingale approach for testing diffusion models based on infinitesimal operator," Journal of Econometrics, Elsevier, vol. 162(2), pages 189-212, June.
    48. A. Craig Burnside & Jeremy J. Graveline, 2012. "On the Asset Market View of Exchange Rates," NBER Working Papers 18646, National Bureau of Economic Research, Inc.
    49. Patrick Cheridito & Damir Filipovic, 2004. "Market Price of Risk Specifications for Affine Models: Theory and Evidence," Econometric Society 2004 North American Winter Meetings 536, Econometric Society.
    50. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    51. Antonio Diez de los Rios, 2006. "Can Affine Term Structure Models Help Us Predict Exchange Rates?," Staff Working Papers 06-27, Bank of Canada.
    52. Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.
    53. Carl Chiarella & Hing Hung & Thuy-Duong To, 2005. "The Volatility Structure of the Fixed Income Market under the HJM Framework: A Nonlinear Filtering Approach," Research Paper Series 151, Quantitative Finance Research Centre, University of Technology, Sydney.
    54. Brandt, Michael W. & Cochrane, John H. & Santa-Clara, Pedro, 2006. "International risk sharing is better than you think, or exchange rates are too smooth," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 671-698, May.
    55. Michael S. Johannes & Nicholas G. Polson & Jonathan R. Stroud, 2009. "Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2559-2599, July.
    56. Yuming Li & Maosen Zhong, 2009. "International asset returns and exchange rates," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 263-285.
    57. Astrid Eisenberg & Markus Rudolf, 2007. "Exchange Rates and the Conversion of Currency‐Specific Risk Premia," European Financial Management, European Financial Management Association, vol. 13(4), pages 672-701, September.
    58. Alexander David & Pietro Veronesi, 2014. "Investors' and Central Bank's Uncertainty Embedded in Index Options," The Review of Financial Studies, Society for Financial Studies, vol. 27(6), pages 1661-1716.
    59. Xiao Huang, 2011. "Quasi‐maximum likelihood estimation of discretely observed diffusions," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 241-256, July.
    60. S. Mouabbi, 2014. "An arbitrage-free Nelson-Siegel term structure model with stochastic volatility for the determination of currency risk premia," Working papers 527, Banque de France.
    61. Guay, François & Schwenkler, Gustavo, 2021. "Efficient estimation and filtering for multivariate jump–diffusions," Journal of Econometrics, Elsevier, vol. 223(1), pages 251-275.
    62. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.
    63. Osnat Stramer & Jun Yan, 2007. "Asymptotics of an Efficient Monte Carlo Estimation for the Transition Density of Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 483-496, December.
    64. Luca Benati, 2006. "Affine term structure models for the foreign exchange risk premium," Bank of England working papers 291, Bank of England.
    65. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    66. 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.
    67. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Teaching an old dog new tricks: Improved estimation of the parameters of SDEs by numerical solution of the Fokker-Planck equation," Stan Hurn Discussion Papers 2006-01, School of Economics and Finance, Queensland University of Technology.
    68. Egorov, Alexei V. & Li, Haitao & Ng, David, 2011. "A tale of two yield curves: Modeling the joint term structure of dollar and euro interest rates," Journal of Econometrics, Elsevier, vol. 162(1), pages 55-70, May.
    69. de Genaro, Alan & Avellaneda, Marco, 2019. "Does the Lending Rate Impact ETF's Prices?," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(2), January.
    70. Singleton, Kenneth J., 2001. "Estimation of affine asset pricing models using the empirical characteristic function," Journal of Econometrics, Elsevier, vol. 102(1), pages 111-141, May.
    71. Brennan, Michael J. & Xia, Yihong, 2004. "International Capital Markets and Foreign Exchange Risk," University of California at Los Angeles, Anderson Graduate School of Management qt53z0s29k, Anderson Graduate School of Management, UCLA.
    72. Jones, Christopher S., 2003. "The dynamics of stochastic volatility: evidence from underlying and options markets," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 181-224.
    73. Cheridito, Patrick & Filipovic, Damir & Kimmel, Robert L., 2007. "Market price of risk specifications for affine models: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 83(1), pages 123-170, January.
    74. Leah Kelly, 2004. "Inference and Intraday Analysis of Diversified World Stock Indices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2004.
    75. 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.
    76. Yin, Weiwei & Li, Junye, 2014. "Macroeconomic fundamentals and the exchange rate dynamics: A no-arbitrage macro-finance approach," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 46-64.
    77. Hong, Yongmiao & Li, Haitao, 2002. "Nonparametric specification testing for continuous-time models with application to spot interest rates," SFB 373 Discussion Papers 2002,32, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    78. Yung, Julieta, 2021. "Can interest rate factors explain exchange rate fluctuations?," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 34-56.
    79. Alexander David & Pietro Veronesi, 2013. "What Ties Return Volatilities to Price Valuations and Fundamentals?," Journal of Political Economy, University of Chicago Press, vol. 121(4), pages 682-746.
    80. Georg Mosburger & Paul Schneider, 2005. "Modelling International Bond Markets with Affine Term Structure Models," Finance 0509003, University Library of Munich, Germany.
    81. Kenc, Turalay & Dibooglu, Sel, 2007. "The spirit of capitalism, asset pricing and growth in a small open economy," Journal of International Money and Finance, Elsevier, vol. 26(8), pages 1378-1402, December.
    82. Fousseni Chabi-Yo & Jun Yang, 2007. "A No-Arbitrage Analysis of Macroeconomic Determinants of Term Structures and the Exchange Rate," Staff Working Papers 07-21, Bank of Canada.
    83. Salima El Kolei & Fabien Navarro, 2022. "Contrast estimation for noisy observations of diffusion processes via closed-form density expansions," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 303-336, July.
    84. Alexander David & Pietro Veronesi, 2009. "What Ties Return Volatilities to Price Valuations and Fundamentals?," NBER Working Papers 15563, National Bureau of Economic Research, Inc.
    85. Ahmet Can Ýnci, 2007. "Currency and yield Co-integration between a developed and an emerging Country: The Case of Turkey," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 21(1+2), pages 1-20.
    86. Siddhartha Chib & Michael K Pitt & Neil Shephard, 2004. "Likelihood based inference for diffusion driven models," Economics Papers 2004-W20, Economics Group, Nuffield College, University of Oxford.
    87. Monica Gentile & Roberto Renò, 2002. "Which Model for the Italian Interest Rates?," LEM Papers Series 2002/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    88. Dolgov, Urij, 2015. "Calibration of Heston's stochastic volatility model to an empirical density using a genetic algorithm," Forschung am ivwKöln 3/2015, Technische Hochschule Köln – University of Applied Sciences, Institute for Insurance Studies.
    89. Antonio Diez de los Rios, 2017. "Optimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear Regressions," Staff Working Papers 17-33, Bank of Canada.
    90. 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.
    91. Alexander David & Pietro Veronesi, 2011. "Investors' and Central Bank's Uncertainty Embedded in Index Options," NBER Working Papers 16764, National Bureau of Economic Research, Inc.
    92. M. Hadzi-Vaskov & C.J.M. Kool, 2007. "Stochastic Discount Factor Approach to International Risk-Sharing:A Robustness Check of the Bilateral Setting," Working Papers 07-34, Utrecht School of Economics.
    93. Marcel Rindisbacher & Jérôme Detemple & René Garcia, 2004. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," Econometric Society 2004 North American Winter Meetings 483, Econometric Society.
    94. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the wood for the trees: A critical evaluation of methods to estimate the parameters of stochastic differential equations," Stan Hurn Discussion Papers 2006, School of Economics and Finance, Queensland University of Technology.
    95. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations. Working paper #2," NCER Working Paper Series 2, National Centre for Econometric Research.
    96. Branger, Nicole & Herold, Michael & Muck, Matthias, 2021. "International stochastic discount factors and covariance risk," Journal of Banking & Finance, Elsevier, vol. 123(C).
    97. Fornari, Fabio & Mele, Antonio, 2006. "Approximating volatility diffusions with CEV-ARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 931-966, June.
    98. Egorov, Alexei V. & Hong, Yongmiao & Li, Haitao, 2006. "Validating forecasts of the joint probability density of bond yields: Can affine models beat random walk?," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 255-284.
    99. Chernov, Mikhail & Graveline, Jeremy & Zviadadze, Irina, 2012. "Sources of Risk in Currency Returns," CEPR Discussion Papers 8745, C.E.P.R. Discussion Papers.
    100. Olesia Verchenko, 2011. "Testing option pricing models: complete and incomplete markets," Discussion Papers 38, Kyiv School of Economics.
    101. Iwata, Shigeru & Wu, Shu, 2009. "Stock market liberalization and international risk sharing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 461-476, July.
    102. Joslin, Scott & Konchitchki, Yaniv, 2018. "Interest rate volatility, the yield curve, and the macroeconomy," Journal of Financial Economics, Elsevier, vol. 128(2), pages 344-362.
    103. Monika Piazzesi, 2001. "An Econometric Model of the Yield Curve with Macroeconomic Jump Effects," NBER Working Papers 8246, National Bureau of Economic Research, Inc.
    104. Sen Dong, 2006. "Monetary Policy Rules and Exchange Rates:A Structural VAR Identified by No Arbitrage," 2006 Meeting Papers 875, Society for Economic Dynamics.
    105. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.
    106. Durham, Garland B., 2003. "Likelihood-based specification analysis of continuous-time models of the short-term interest rate," Journal of Financial Economics, Elsevier, vol. 70(3), pages 463-487, December.

  16. Michael W. Brandt & John H. Cochrane & Pedro Santa-Clara, 2001. "International Risk Sharing is Better Than You Think (or Exchange Rates are Much Too Smooth)," NBER Working Papers 8404, National Bureau of Economic Research, Inc.

    Cited by:

    1. Pavlova, Anna & Rigobon, Roberto, 2004. "Asset Prices and Exchange Rates," Working papers 4322-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Cappiello, Lorenzo & De Santis, Roberto A., 2005. "Explaining exchange rate dynamics: the uncovered equity return parity condition," Working Paper Series 529, European Central Bank.
    3. Ravi Bansal, 2007. "Long-run risks and financial markets," Review, Federal Reserve Bank of St. Louis, vol. 89(Jul), pages 283-300.
    4. Narayana R. Kocherlakota & Luigi Pistaferri, 2007. "Household Heterogeneity and Real Exchange Rates," Economic Journal, Royal Economic Society, vol. 117(519), pages 1-25, March.
    5. Roche, M.J. & Moore. M.J., 2002. "Volatile and persistent real exchange rates without the contrivance of sticky prices," Economics Department Working Paper Series n1160402, Department of Economics, National University of Ireland - Maynooth.
    6. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    7. Shu Wu, 2007. "Interest Rate Risk and the Forward Premium Anomaly in Foreign Exchange Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2-3), pages 423-442, March.
    8. Hanno Lustig, 2005. "Investing in Foreign Currency is like Betting on your Intertemporal Marginal Rate of Substitution (joint with Adrien Verdelhan, BU, forthcoming in Papers and Proceedings JEEA)," UCLA Economics Online Papers 368, UCLA Department of Economics.
    9. Nikolaos Panigirtzoglou, 2004. "Implied Foreign Exchange Risk Premia," European Financial Management, European Financial Management Association, vol. 10(2), pages 321-338, June.
    10. Timothy K. Chue, 2004. "The Spirit of Capitalism and International Risk Sharing," Econometric Society 2004 Far Eastern Meetings 589, Econometric Society.
    11. Michael W. Brandt & Pedro Santa-Clara, 2001. "Simulated Likelihood Estimation of Diffusions with an Application to Exchange Rate Dynamics in Incomplete Markets," NBER Technical Working Papers 0274, National Bureau of Economic Research, Inc.

  17. Longstaff, Francis A & Santa-Clara, Pedro & Schwartz, Eduardo S, 2000. "The Relative Valuation of Caps and Swaptions: Theory and Empirical Evidence," University of California at Los Angeles, Anderson Graduate School of Management qt65f1914p, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Jagannathan, Ravi & Kaplin, Andrew & Sun, Steve, 2003. "An evaluation of multi-factor CIR models using LIBOR, swap rates, and cap and swaption prices," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 113-146.
    2. Jun Liu & Francis A. Longstaff & Ravit E. Mandell, 2002. "The Market Price of Credit Risk: An Empirical Analysis of Interest Rate Swap Spreads," NBER Working Papers 8990, National Bureau of Economic Research, Inc.
    3. Frank De Jong & Joost Driessen & Antoon Pelsser, 2001. "Libor Market Models versus Swap Market Models for Pricing Interest Rate Derivatives: An Empirical Analysis," Review of Finance, European Finance Association, vol. 5(3), pages 201-237.
    4. Matthew Pritsker, 2005. "Large investors: implications for equilibrium asset, returns, shock absorption, and liquidity," Finance and Economics Discussion Series 2005-36, Board of Governors of the Federal Reserve System (U.S.).
    5. Qiang Dai & Kenneth J. Singleton, 2001. "Expectation Puzzles, Time-varying Risk Premia, and Dynamic Models of the Term Structure," NBER Working Papers 8167, National Bureau of Economic Research, Inc.

  18. Ledoit, Olivier & Santa-Clara, Pedro & Wolf, Michael, 1999. "Flexible Multivariate GARCH Modeling With an Application to International Stock Markets," University of California at Los Angeles, Anderson Graduate School of Management qt93s6p8gb, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Matmoura, Yassine & Penev, Spiridon, 2013. "Multistage optimization of option portfolio using higher order coherent risk measures," European Journal of Operational Research, Elsevier, vol. 227(1), pages 190-198.
    2. Marfatia, Hardik A., 2017. "A fresh look at integration of risks in the international stock markets: A wavelet approach," Review of Financial Economics, Elsevier, vol. 34(C), pages 33-49.
    3. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    4. Kilian, Lutz & Gonçalves, Sílvia, 2002. "Bootstrapping Autoregressions with Conditional Heteroskedasticity of Unknown Form," Discussion Paper Series 1: Economic Studies 2002,26, Deutsche Bundesbank.
    5. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    6. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
    7. Redouane Elkamhia & Denitsa Stefanova, 2011. "Dynamic Correlation or Tail Dependence Hedging for Portfolio Selection," Tinbergen Institute Discussion Papers 11-028/2/DSF10, Tinbergen Institute.
    8. Magdalena Vorzsak & Carmen Maria Gut, 2008. "Constraints Concerning Investment And Participation In Professional Training In The Companies From The Romanian Manufacturing Industry," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    9. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    10. Palandri, Alessandro, 2009. "Sequential conditional correlations: Inference and evaluation," Journal of Econometrics, Elsevier, vol. 153(2), pages 122-132, December.
    11. Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers 320, Institute for Empirical Research in Economics - University of Zurich.
    12. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    13. Olivier Ledoit & Michael Wolf, 2018. "Robust performance hypothesis testing with smooth functions of population moments," ECON - Working Papers 305, Department of Economics - University of Zurich.
    14. Pesaran, M. Hashem & Zaffaroni, Paolo, 2005. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management," CEPR Discussion Papers 5279, C.E.P.R. Discussion Papers.
    15. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    16. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    17. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
    18. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.
    19. Tiberiu Cristian Avramescu, 2008. "Romanian Tourism: A Regional Approach," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    20. Šárka Brychtová, 2008. "Spa Healing Sources In Czech Republic," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    21. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    22. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    23. Li, Chenxing & Maheu, John M, 2020. "A Multivariate GARCH-Jump Mixture Model," MPRA Paper 104770, University Library of Munich, Germany.
    24. Asl, Mahdi Ghaemi & Canarella, Giorgio & Miller, Stephen M., 2021. "Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies," Resources Policy, Elsevier, vol. 71(C).
    25. Kumiega, Andrew & Neururer, Thaddeus & Van Vliet, Ben, 2011. "Independent component analysis for realized volatility: Analysis of the stock market crash of 2008," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 292-302, June.
    26. Zhou, Jian, 2014. "Modeling conditional covariance for mixed-asset portfolios," Economic Modelling, Elsevier, vol. 40(C), pages 242-249.
    27. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    28. Sangwon Suh & Inwon Jang & Misun Ahn, 2013. "A Simple Method For Measuring Systemic Risk Using Credit Default Swap Market Data," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(4), pages 75-100, December.
    29. Manole Velicanu & Gheorghe Matei, 2008. "Decision Support Systems: Present And Future Trends," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    30. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    31. Sarwar, Suleman & Khalfaoui, Rabeh & Waheed, Rida & Dastgerdi, Hamidreza Ghorbani, 2019. "Volatility spillovers and hedging: Evidence from Asian oil-importing countries," Resources Policy, Elsevier, vol. 61(C), pages 479-488.
    32. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    33. Jan Ericsson & Kris Jacobs & Rodolfo A. Oviedo, 2004. "The Determinants of Credit Default Swap Premia," CIRANO Working Papers 2004s-55, CIRANO.
    34. Cristina Silvia Nistor & Crina Ioana Filip & Adela Deaconu, 2008. "Derivative Instruments – Alternatives To Cover The Foreign Exchange Rate In The Case Of Import-Export Operations - Accounting Approach For Romania," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    35. Peter Reinhard Hansen & Guillaume Horel & Asger Lunde & Ilya Archakov, 2015. "A Markov Chain Estimator of Multivariate Volatility from High Frequency Data," CREATES Research Papers 2015-19, Department of Economics and Business Economics, Aarhus University.
    36. Gribisch, Bastian, 2013. "A latent dynamic factor approach to forecasting multivariate stock market volatility," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79823, Verein für Socialpolitik / German Economic Association.
    37. Cristina Curutiu, 2008. "Methods Of Portfolio Management - A Review Of Literature -," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    38. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    39. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    40. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    41. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
    42. Audrino, Francesco & Trojani, Fabio, 2011. "A General Multivariate Threshold GARCH Model With Dynamic Conditional Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 138-149.
    43. Hafner, Christian M. & Reznikova, Olga, 2012. "On the estimation of dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3533-3545.
    44. Suh, Sangwon, 2012. "Measuring systemic risk: A factor-augmented correlated default approach," Journal of Financial Intermediation, Elsevier, vol. 21(2), pages 341-358.
    45. Claudio Morana, 2016. "Macroeconomic and Financial Effects of Oil Price Shocks: Evidence for the Euro Area," Working Papers 2016.23, Fondazione Eni Enrico Mattei.
    46. Matthew J. Lebo & Janet M. Box‐Steffensmeier, 2008. "Dynamic Conditional Correlations in Political Science," American Journal of Political Science, John Wiley & Sons, vol. 52(3), pages 688-704, July.
    47. 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.
    48. Chulwoo Han & Frank C. Park & Jangkoo Kang, 2017. "A geometric treatment of time-varying volatilities," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 1121-1141, November.
    49. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    50. Laurent-Emmanuel Calvet & Adlai J. Fisher & Samuel B. Thompson, 2006. "Volatility Comovement: a multifrequency approach," Post-Print hal-00459667, HAL.
    51. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    52. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    53. 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.
    54. Denis Pelletier, 2004. "Regime Switching for Dynamic Correlations," Econometric Society 2004 North American Summer Meetings 230, Econometric Society.
    55. 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.
    56. Farhat Iqbal, 2013. "Robust estimation of the simplified multivariate GARCH model," Empirical Economics, Springer, vol. 44(3), pages 1353-1372, June.
    57. Jaroslava HLOUSKOVA & Kurt SCHMIDHEINY & Martin WAGNER, 2004. "Multistep Predictions for Multivariate GARCH Models: Closed Form Solution and the Value for Portfolio Management," Cahiers de Recherches Economiques du Département d'économie 04.10, Université de Lausanne, Faculté des HEC, Département d’économie.
    58. Gang-Zhi Fan & Zsuzsa Huszár & Weina Zhang, 2013. "The Relationships between Real Estate Price and Expected Financial Asset Risk and Return: Theory and Empirical Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 46(4), pages 568-595, May.
    59. Evelyn Benvin & Solange Berstein & Olga Fuentes & Jorge Miranda & Nicolás Torrealba & Mario Vera, 2009. "Carteras Referenciales y Esquema de Premios y Castigos para los Fondos de Cesantía," Working Papers 34, Superintendencia de Pensiones, revised Jan 2012.
    60. Zouheir Mighri & Faysal Mansouri, 2013. "Dynamic Conditional Correlation Analysis of Stock Market Contagion: Evidence from the 2007-2010 Financial Crises," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 637-661.
    61. Zhang, Zhengjun & Huang, James, 2006. "Extremal financial risk models and portfolio evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2313-2338, December.
    62. Perignon, Christophe & Smith, Daniel R. & Villa, Christophe, 2007. "Why common factors in international bond returns are not so common," Journal of International Money and Finance, Elsevier, vol. 26(2), pages 284-304, March.
    63. Paul Ehling & Christian Heyerdahl-Larsen, 2014. "Correlations," Working Papers 1413, Banco de España.
    64. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
    65. Gad, Samar & Andrikopoulos, Panagiotis, 2019. "Diversification benefits of Shari'ah compliant equity ETFs in emerging markets," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 133-144.
    66. Katsiampa, Paraskevi, 2019. "Volatility co-movement between Bitcoin and Ether," Finance Research Letters, Elsevier, vol. 30(C), pages 221-227.
    67. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    68. Denitsa Stefanova, 2012. "Stock Market Asymmetries: A Copula Diffusion," Tinbergen Institute Discussion Papers 12-125/IV/DSF45, Tinbergen Institute.
    69. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    70. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    71. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    72. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    73. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper series 66_13, Rimini Centre for Economic Analysis.
    74. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    75. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    76. Mihaela Dragan & Zenovia Cristiana Pop, 2008. "CRITERIA FOR PRODUCT QUALITY IN THE FRAME OF INTERCULTURAL MARKET STRATEGIES OF SMALL AND MEDIUM SIZED ENTERPRISES - a brief review of literature -," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    77. Lim, Siew Hoon & Turner, Peter A., 2016. "Airline Fuel Hedging: Do Hedge Horizon and Contract Maturity Matter?," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 55(1), April.
    78. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    79. Bal??zs ??gert & Ev??en Kocenda, 2007. "Time-Varying Comovements in Developed and Emerging European Stock Markets: Evidence from Intraday Data," William Davidson Institute Working Papers Series wp861, William Davidson Institute at the University of Michigan.
    80. Braione, Manuela & Scholtes, Nicolas K., 2014. "Construction of value-at-risk forecasts under different distributional assumptions within a BEKK framework," LIDAM Discussion Papers CORE 2014059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    81. Villalba Padilla, Fátima Irina & Flores-Ortega, Miguel, 2014. "Análisis de la volatilidad del índice principal del mercado bursátil mexicano, del índice de riesgo país y de la mezcla mexicana de exportación mediante un modelo GARCH trivariado asimétrico || Volati," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 17(1), pages 3-22, June.
    82. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    83. Hardik A. Marfatia, 2017. "A fresh look at integration of risks in the international stock markets: A wavelet approach," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 33-49, September.
    84. Gautam Sabnis & Debdeep Pati & Anirban Bhattacharya, 2019. "Compressed Covariance Estimation with Automated Dimension Learning," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 466-481, December.
    85. Kawakatsu, Hiroyuki, 2006. "Matrix exponential GARCH," Journal of Econometrics, Elsevier, vol. 134(1), pages 95-128, September.
    86. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    87. Partenie Dumbrava & Ioan Pop & Eniko Fazakas & Jozsef Fazakas & Ludovica Breban, 2008. "The Environmental Impact Of Beer Production," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    88. Loann David Denis Desboulets, 2017. "Co-movements in Market Prices and Fundamentals: A Semiparametric Multivariate GARCH Approach," Working Papers halshs-02059302, HAL.
    89. Suh, Sangwon, 2015. "Measuring sovereign risk contagion in the Eurozone," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 45-65.
    90. Paramita Mukherjee, 2011. "An exploration on volatility across India and some developed and emerging equity markets," Asia-Pacific Development Journal, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), vol. 18(2), pages 79-103, December.
    91. Chiu, Mei Choi & Wong, Hoi Ying, 2014. "Mean–variance asset–liability management with asset correlation risk and insurance liabilities," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 300-310.
    92. Philipp Adämmer & Martin T. Bohl, 2018. "Price discovery dynamics in European agricultural markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(5), pages 549-562, May.
    93. Hafner, Christian & Herwartz, Helmut, 2022. "Asymmetric volatility impulse response functions," LIDAM Discussion Papers ISBA 2022037, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    94. Christodoulakis, George A., 2007. "Common volatility and correlation clustering in asset returns," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1263-1284, November.
    95. Kwan, Clarence C.Y., 2008. "Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices," Finance Research Letters, Elsevier, vol. 5(4), pages 236-244, December.
    96. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    97. Kin-Yip Ho & Ka Cheng Tsui, 2004. "Volatility Dynamics of the Tokyo Stock Exchange: A Sectoral Analysis based on the Multivariate GARCH Approach," Money Macro and Finance (MMF) Research Group Conference 2004 12, Money Macro and Finance Research Group.
    98. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    99. Mr. Jorge A Chan-Lau & Ms. Srobona Mitra & Ms. Li L Ong, 2007. "Contagion Risk in the International Banking System and Implications for London As a Global Financial Center," IMF Working Papers 2007/074, International Monetary Fund.
    100. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    101. 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.
    102. Zhou, Xinmiao & Zhang, Junru & Zhang, Zhaoyong, 2021. "How does news flow affect cross-market volatility spillovers? Evidence from China’s stock index futures and spot markets," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 196-213.
    103. Audrino, Francesco, 2006. "The impact of general non-parametric volatility functions in multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3032-3052, July.
    104. Cevdet Aydemir, A., 2008. "Risk sharing and counter-cyclical variation in market correlations," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3084-3112, October.
    105. Adina Negrusa & Oana Adriana Gica, 2008. "Analysis Of Potential Sme’S Role For Developing Tourism In Transylvania," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    106. Giovanni Barone-Adesi & Francesco Audrino, 2006. "Average conditional correlation and tree structures for multivariate GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 579-600.
    107. Panayiotis F. Diamandis & Anastassios A. Drakos & Georgios P. Kouretas & Leonidas P. Zarangas, 2012. "Asset allocation in the Athens stock exchange: a variance sensitivity analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 17(2), pages 167-181, April.
    108. Cardinali Alessandro & Nason Guy P, 2011. "Costationarity of Locally Stationary Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 2(2), pages 1-35, January.
    109. Yongseok Shin & Ms. Rachel Glennerster, 2003. "Is Transparency Good for You, and Can the IMF Help?," IMF Working Papers 2003/132, International Monetary Fund.
    110. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    111. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    112. Wang, Jiazhen & Jiang, Yuexiang & Zhu, Yanjian & Yu, Jing, 2020. "Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 91(C), pages 428-444.
    113. Harris, Richard D.F. & Mazibas, Murat, 2010. "Dynamic hedge fund portfolio construction," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 351-357, December.
    114. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.
    115. Pan, Zhiyuan & Wang, Yudong & Liu, Li, 2016. "The relationships between petroleum and stock returns: An asymmetric dynamic equi-correlation approach," Energy Economics, Elsevier, vol. 56(C), pages 453-463.
    116. Jon Wongswan, 2003. "Contagion: an empirical test," International Finance Discussion Papers 775, Board of Governors of the Federal Reserve System (U.S.).
    117. Adrian Grosanu & Paula Ramona Rachisan, 2008. "The Implementation Of Profit Centres Inside An Economic Entity," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    118. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
    119. Hafner, Christian M. & Herwartz, Helmut, 2023. "Asymmetric volatility impulse response functions," Economics Letters, Elsevier, vol. 222(C).
    120. Lee, Hsiang-Tai, 2010. "Regime switching correlation hedging," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2728-2741, November.

  19. P. Santa-Clara & D. Sornette, 1998. "The Dynamics of the Forward Interest Rate Curve with Stochastic String Shocks," Papers cond-mat/9801321, arXiv.org.

    Cited by:

    1. Heidari, Massoud & Wu, Liuren, 2009. "A Joint Framework for Consistently Pricing Interest Rates and Interest Rate Derivatives," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(3), pages 517-550, June.
    2. Longstaff, Francis A., 2002. "Optimal Recursive Refinancing and the Valuation of Mortgage-Backed Securities," University of California at Los Angeles, Anderson Graduate School of Management qt19k7479t, Anderson Graduate School of Management, UCLA.
    3. Kristensen, Dennis, 2004. "A semiparametric single-factor model of the term structure," LSE Research Online Documents on Economics 24741, London School of Economics and Political Science, LSE Library.
    4. Robert Jarrow & Haitao Li & Feng Zhao, 2007. "Interest Rate Caps “Smile” Too! But Can the LIBOR Market Models Capture the Smile?," Journal of Finance, American Finance Association, vol. 62(1), pages 345-382, February.
    5. Kimmel, Robert L., 2004. "Modeling the term structure of interest rates: A new approach," Journal of Financial Economics, Elsevier, vol. 72(1), pages 143-183, April.
    6. Qiang Dai & Kenneth Singleton, 2003. "Term Structure Dynamics in Theory and Reality," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 631-678, July.
    7. Andrea Roncoroni & Stefano Galluccio & Paolo Guiotto, 2010. "Shape factors and cross-sectional risk," Post-Print hal-00736733, HAL.
    8. Roger Lord & Antoon Pelsser, 2005. "Level-Slope-Curvature - Fact or Artefact?," Tinbergen Institute Discussion Papers 05-083/2, Tinbergen Institute.
    9. Demers, Jean-Guy, 2009. "Multiple zone power forwards: A value at risk framework," Energy Economics, Elsevier, vol. 31(5), pages 714-726, September.
    10. Buraschi, Andrea & Corielli, Francesco, 2005. "Risk management implications of time-inconsistency: Model updating and recalibration of no-arbitrage models," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2883-2907, November.
    11. Lloyd P. Blenman & Alberto Bueno-Guerrero & Steven P. Clark, 2022. "Pricing and Hedging Bond Power Exchange Options in a Stochastic String Term-Structure Model," Risks, MDPI, vol. 10(10), pages 1-17, September.
    12. Belal E. Baaquie & Marakani Srikant & Mitch C. Warachka, 2003. "A Quantum Field Theory Term Structure Model Applied to Hedging," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 6(05), pages 443-467.
    13. Laruent Barras, 2005. "International Conditional Asset Allocation under Real Time Uncertrainty," FAME Research Paper Series rp153, International Center for Financial Asset Management and Engineering.
    14. Pandher, Gurupdesh, 2007. "Arbitrage-free valuation of interest rate securities under forward curves with stochastic speed and acceleration," Journal of Economic Theory, Elsevier, vol. 137(1), pages 432-459, November.
    15. Dai, Qiang & Singleton, Kenneth J., 2003. "Fixed-income pricing," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 20, pages 1207-1246, Elsevier.
    16. Kerkhof, F.L.J. & Pelsser, A., 2002. "Observational Equivalence of Discrete String Models and Market Models," Other publications TiSEM adbe78f4-8729-4f92-ba2b-6, Tilburg University, School of Economics and Management.
    17. Bueno-Guerrero, Alberto & Moreno, Manuel & Navas, Javier F., 2016. "The stochastic string model as a unifying theory of the term structure of interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 217-237.
    18. Pierre Collin‐Dufresne & Robert S. Goldstein, 2002. "Do Bonds Span the Fixed Income Markets? Theory and Evidence for Unspanned Stochastic Volatility," Journal of Finance, American Finance Association, vol. 57(4), pages 1685-1730, August.
    19. Francis A. Longstaff, 2004. "Optimal Recursive Refinancing and the Valuation of Mortgage-Backed Securities," NBER Working Papers 10422, National Bureau of Economic Research, Inc.
    20. Vladislav Kargin, 2003. "Portfolio Management for a Random Field of Bond Returns," Finance 0310007, University Library of Munich, Germany.
    21. W. -X. Zhou & D. Sornette, 2003. "Causal Slaving of the U.S. Treasury Bond Yield Antibubble by the Stock Market Antibubble of August 2000," Papers cond-mat/0312658, arXiv.org.
    22. Roberto Baviera, 2007. "A simple solution for sticky cap and sticky floor," Quantitative Finance, Taylor & Francis Journals, vol. 7(3), pages 285-287.
    23. Svenstrup, Mikkel, 2005. "On the suboptimality of single-factor exercise strategies for Bermudan swaptions," Journal of Financial Economics, Elsevier, vol. 78(3), pages 651-684, December.
    24. Rajinda Wickrama, 2021. "Pricing Exchange Rate Options and Quanto Caps in the Cross-Currency Random Field LIBOR Market Model," Papers 2103.00323, arXiv.org, revised Mar 2021.
    25. Hassan Allouba & Victor Goodman, 2010. "Market Price of Risk and Random Field Driven Models of Term Structure: A Space-Time Change of Measure Look," Papers 1005.3799, arXiv.org.
    26. Alberto Bueno-Guerrero & Steven P. Clark, 2023. "Option Pricing under a Generalized Black–Scholes Model with Stochastic Interest Rates, Stochastic Strings, and Lévy Jumps," Mathematics, MDPI, vol. 12(1), pages 1-39, December.
    27. Richard K. Crump & Nikolay Gospodinov, 2022. "On the Factor Structure of Bond Returns," Econometrica, Econometric Society, vol. 90(1), pages 295-314, January.
    28. Frank de Jong & Joost Driessen & Antoon Pelsser, 2004. "On the Information in the Interest Rate Term Structure and Option Prices," Review of Derivatives Research, Springer, vol. 7(2), pages 99-127, August.
    29. Christophe PÉRIGNON & Christophe VILLA, 2002. "Permanent and Transitory Factors Affecting the Dynamics of the Term Structure of Interest Rates," FAME Research Paper Series rp53, International Center for Financial Asset Management and Engineering.
    30. Belal Baaquie & Jean-Philippe Bouchaud, 2004. ""Stiff" Field Theory of Interest Rates and Psychological Future Time," Science & Finance (CFM) working paper archive 500064, Science & Finance, Capital Fund Management.
    31. Mele, Antonio & Distaso, Walter & Vilkov, Grigory, 2019. "Correlation Risk, Strings and Asset Prices," CEPR Discussion Papers 13873, C.E.P.R. Discussion Papers.
    32. Bueno-Guerrero, Alberto & Moreno, Manuel & Navas, Javier F., 2015. "Stochastic string models with continuous semimartingales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 229-246.
    33. Driessen, Joost & Klaassen, Pieter & Melenberg, Bertrand, 2003. "The Performance of Multi-Factor Term Structure Models for Pricing and Hedging Caps and Swaptions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(3), pages 635-672, September.
    34. Bisht Deepak & Laha, A. K., 2017. "Pricing Option on Commodity Futures under String Shock," IIMA Working Papers WP 2017-07-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    35. Choong Tze Chua & Dean Foster & Krishna Ramaswamy & Robert Stine, 2008. "A Dynamic Model for the Forward Curve," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 265-310, January.
    36. Suresh M. Sundaresan, 2000. "Continuous‐Time Methods in Finance: A Review and an Assessment," Journal of Finance, American Finance Association, vol. 55(4), pages 1569-1622, August.
    37. Longstaff, Francis A. & Santa-Clara, Pedro & Schwartz, Eduardo S., 2001. "Throwing away a billion dollars: the cost of suboptimal exercise strategies in the swaptions market," Journal of Financial Economics, Elsevier, vol. 62(1), pages 39-66, October.
    38. Eymen Errais & Fabio Mercurio, 2005. "Yes, Libor Models can capture Interest Rate Derivatives Skew : A Simple Modelling Approach," Computing in Economics and Finance 2005 192, Society for Computational Economics.
    39. Vladislav Kargin, 2002. "On Bond Portfolio Management," Papers math/0208130, arXiv.org, revised Mar 2003.
    40. Sergey Lototsky & Henry Schellhorn & Ran Zhao, 2016. "A String Model of Liquidity in Financial Markets," Papers 1608.05900, arXiv.org, revised Apr 2018.
    41. Belal E. Baaquie & Marakani Srikant & Mitch Warachka, 2002. "A Quantum Field Theory Term Structure Model Applied to Hedging," Papers cond-mat/0206457, arXiv.org.
    42. Belal Baaquie & Jean-Philippe Bouchaud, 2004. ""Stiff" Field Theory of Interest Rates and Psychological Future Time," Papers cond-mat/0403713, arXiv.org.
    43. Robert A. Jarrow, 2009. "The Term Structure of Interest Rates," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 69-96, November.
    44. Bibinger, Markus & Trabs, Mathias, 2020. "Volatility estimation for stochastic PDEs using high-frequency observations," Stochastic Processes and their Applications, Elsevier, vol. 130(5), pages 3005-3052.
    45. Andrew Jeffrey, 2004. "Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 251-289.
    46. Feng Zhao & Robert Jarrow & Haitao Li, 2004. "Interest Rate Caps Smile Too! But Can the LIBOR Market Models Capture It?," Econometric Society 2004 North American Winter Meetings 431, Econometric Society.
    47. Ledoit, Olivier & Santa-Clara, Pedro & Yan, Shu, 2002. "Relative Pricing of Options with Stochastic Volatility," University of California at Los Angeles, Anderson Graduate School of Management qt7jp8f42t, Anderson Graduate School of Management, UCLA.
    48. Bueno-Guerrero, Alberto & Moreno, Manuel & Navas, Javier F., 2020. "Valuation of caps and swaptions under a stochastic string model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    49. Casassus, Jaime & Collin-Dufresne, Pierre & Goldstein, Bob, 2005. "Unspanned stochastic volatility and fixed income derivatives pricing," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2723-2749, November.
    50. Duffie, Darrell, 2003. "Intertemporal asset pricing theory," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 11, pages 639-742, Elsevier.

  20. Santa-Clara, Pedro, 1997. "Simulated Likeliehood Estimation of Diffusions With an Application to the Short Tem Interest Rate," University of California at Los Angeles, Anderson Graduate School of Management qt8zz2d0q8, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Sun, Libo & Lee, Chihoon & Hoeting, Jennifer A., 2015. "A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 54-67.

Articles

  1. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Momentum has its moments," Journal of Financial Economics, Elsevier, vol. 116(1), pages 111-120.

    Cited by:

    1. Klaus Grobys & Topi Huhta-Halkola, 2019. "Combining value and momentum: evidence from the Nordic equity market," Applied Economics, Taylor & Francis Journals, vol. 51(26), pages 2872-2884, June.
    2. Butt, Hilal Anwar & Virk, Nader Shahzad, 2019. "Market downturns, zero investment strategies and systematic liquidity risk," Finance Research Letters, Elsevier, vol. 28(C), pages 246-253.
    3. Yang, Xuebing & Zhang, Huilan, 2019. "Extreme absolute strength of stocks and performance of momentum strategies," Journal of Financial Markets, Elsevier, vol. 44(C), pages 71-90.
    4. Yamani, Ehab, 2019. "Diversification role of currency momentum for carry trade: Evidence from financial crises," Journal of Multinational Financial Management, Elsevier, vol. 49(C), pages 1-19.
    5. Fernando F. Ferreira & A. Christian Silva & Ju-Yi Yen, 2019. "Detailed study of a moving average trading rule," Papers 1907.00212, arXiv.org.
    6. Lou, Dong & Polk, Christopher, 2022. "Comomentum: inferring arbitrage activity from return correlations," LSE Research Online Documents on Economics 109318, London School of Economics and Political Science, LSE Library.
    7. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
    8. Michael Pinelis & David Ruppert, 2020. "Machine Learning Portfolio Allocation," Papers 2003.00656, arXiv.org, revised Nov 2021.
    9. Klaus Grobys & James W. Kolari & Jere Rutanen, 2022. "Factor momentum, option-implied volatility scaling, and investor sentiment," Journal of Asset Management, Palgrave Macmillan, vol. 23(2), pages 138-155, March.
    10. Sina Ehsani & Juhani T. Linnainmaa, 2019. "Factor Momentum and the Momentum Factor," NBER Working Papers 25551, National Bureau of Economic Research, Inc.
    11. Fang, Yan & Yuan, Jie & Yang, J. Jimmy & Ying, Shangjun, 2022. "Crash-based quantitative trading strategies: Perspective of behavioral finance," Finance Research Letters, Elsevier, vol. 45(C).
    12. Baltzer, Markus & Jank, Stephan & Smajlbegovic, Esad, 2019. "Who trades on momentum?," Journal of Financial Markets, Elsevier, vol. 42(C), pages 56-74.
    13. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    14. Dierkes, Maik & Krupski, Jan, 2022. "Isolating momentum crashes," Journal of Empirical Finance, Elsevier, vol. 66(C), pages 1-22.
    15. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight Momentum, Informational Shocks, and Late-Informed Trading in China," MPRA Paper 96784, University Library of Munich, Germany.
    16. Philip Nadler & Alessio Sancetta, 2023. "Empirical Asset Pricing with Functional Factors," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1258-1281.
    17. Abhishek Subramanian & Parthajit Kayal, 2023. "Application of Volatility-Managed Portfolios in the Context of a Volatility Index," Working Papers 2023-242, Madras School of Economics,Chennai,India.
    18. Daniel, Kent & Moskowitz, Tobias J., 2016. "Momentum crashes," Journal of Financial Economics, Elsevier, vol. 122(2), pages 221-247.
    19. Subrahmanyam, Avanidhar, 2018. "Equity market momentum: A synthesis of the literature and suggestions for future work," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 291-296.
    20. Jangkoo Kang & Kyung Yoon Kwon, 2021. "Volatility‐managed commodity futures portfolios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 159-178, February.
    21. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    22. Lin, Qi, 2019. "Residual momentum and the cross-section of stock returns: Chinese evidence," Finance Research Letters, Elsevier, vol. 29(C), pages 206-215.
    23. Kobana Abukari & Isaac Otchere, 2020. "Dominance of hybrid contratum strategies over momentum and contrarian strategies: half a century of evidence," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(4), pages 471-505, December.
    24. Kai Li & Jun Liu, 2016. "Reversing Momentum: The Optimal Dynamic Momentum Strategy," Research Paper Series 370, Quantitative Finance Research Centre, University of Technology, Sydney.
    25. Adam Zaremba & George Kambouris, 2019. "The sources of momentum in international government bond returns," Applied Economics, Taylor & Francis Journals, vol. 51(8), pages 848-857, February.
    26. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    27. Ming Gu & Minxing Sun & Yangru Wu & Weike Xu, 2021. "Economic policy uncertainty and momentum," Financial Management, Financial Management Association International, vol. 50(1), pages 237-259, March.
    28. 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.
    29. Fan, Minyou & Li, Youwei & Liu, Jiadong, 2017. "Risk adjusted momentum strategies: a comparison between constant and dynamic volatility scaling approaches," MPRA Paper 83510, University Library of Munich, Germany.
    30. Xingyue Pu & Stephen Roberts & Xiaowen Dong & Stefan Zohren, 2023. "Network Momentum across Asset Classes," Papers 2308.11294, arXiv.org.
    31. Li, Xingjian & Feng, Hongrui & Yan, Shu & Wang, Heng, 2021. "Dispersion in analysts’ target prices and stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    32. Li, Lifang & Galvani, Valentina, 2018. "Market states, sentiment, and momentum in the corporate bond market," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 249-265.
    33. 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.
    34. Nicholas Apergis & Vasilios Plakandaras & Ioannis Pragidis, 2022. "Industry momentum and reversals in stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3093-3138, July.
    35. Chen, Tsung-Yu & Chou, Pin-Huang & Ko, Kuan-Cheng & Rhee, S. Ghon, 2021. "Non-parametric momentum based on ranks and signs," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 94-109.
    36. Li, Kai, 2021. "Nonlinear effect of sentiment on momentum," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    37. Zhu, Zhaobo & Sun, Licheng & Yung, Kenneth & Chen, Min, 2020. "Limited investor attention, relative fundamental strength, and the cross-section of stock returns," The British Accounting Review, Elsevier, vol. 52(4).
    38. Fernando F. Ferreira & A. Christian Silva & Ju-Yi Yen, 2014. "Information ratio analysis of momentum strategies," Papers 1402.3030, arXiv.org, revised Jul 2014.
    39. Vasudevan, Ellapulli V., 2023. "Some gains are riskier than others: Volatility changes and the disposition effect," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 68-81.
    40. Bochuan Dai & Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2021. "Risk reduction using trailing stop‐loss rules," International Review of Finance, International Review of Finance Ltd., vol. 21(4), pages 1334-1352, December.
    41. Ling, Aifan & Huang, Xinrui & Ling, Boya (Vivye), 2022. "Fund immunity to the COVID-19 pandemic: Evidence from Chinese equity funds," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    42. Chang, Jeffery (Jinfan) & Du, Huancheng & Lou, Dong & Polk, Christopher, 2022. "Ripples into waves: Trade networks, economic activity, and asset prices," Journal of Financial Economics, Elsevier, vol. 145(1), pages 217-238.
    43. Bradrania, Reza & Wu, Winston, 2023. "Foreign institutions, local investors and momentum trading," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 40-64.
    44. 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.
    45. Gao, Yang & Leung, Henry & Satchell, Stephen, 2022. "Partial moment momentum," Journal of Banking & Finance, Elsevier, vol. 135(C).
    46. Nazaire, Gregory & Pacurar, Maria & Sy, Oumar, 2021. "Factor Investing and Risk Management: Is Smart-Beta Diversification Smart?," Finance Research Letters, Elsevier, vol. 41(C).
    47. Sirio Aramonte & Mohammad Jahan-Parvar & Samuel Rosen & John W. Schindler, 2021. "Firm-specific risk-neutral distributions with options and CDS," BIS Working Papers 921, Bank for International Settlements.
    48. Docherty, Paul & Hurst, Gareth, 2018. "Return dispersion and conditional momentum returns: International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 263-278.
    49. L. Lin & M. Schatz & D. Sornette, 2019. "A simple mechanism for financial bubbles: time-varying momentum horizon," Quantitative Finance, Taylor & Francis Journals, vol. 19(6), pages 937-959, June.
    50. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    51. Pätäri, Eero & Karell, Ville & Luukka, Pasi & Yeomans, Julian S, 2018. "Comparison of the multicriteria decision-making methods for equity portfolio selection: The U.S. evidence," European Journal of Operational Research, Elsevier, vol. 265(2), pages 655-672.
    52. Demirer, Rıza & Yuksel, Asli & Yuksel, Aydin, 2017. "Flight to quality and the predictability of reversals: The role of market states and global factors," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1445-1454.
    53. Simarjeet Singh & Nidhi Walia, 2022. "Momentum investing: a systematic literature review and bibliometric analysis," Management Review Quarterly, Springer, vol. 72(1), pages 87-113, February.
    54. de Oliveira Souza, Thiago, 2019. "A critique of momentum anomalies," Discussion Papers on Economics 5/2019, University of Southern Denmark, Department of Economics.
    55. Pätäri, Eero & Ahmed, Sheraz & Luukka, Pasi & Yeomans, Julian Scott, 2023. "Can monthly-return rank order reveal a hidden dimension of momentum? The post-cost evidence from the U.S. stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    56. Li Lin & Didier Sornette, 2016. "A Simple Mechanism for Financial Bubbles: Time-Varying Momentum Horizon," Swiss Finance Institute Research Paper Series 16-61, Swiss Finance Institute.
    57. Tzouvanas, Panagiotis & Kizys, Renatas & Tsend-Ayush, Bayasgalan, 2020. "Momentum trading in cryptocurrencies: Short-term returns and diversification benefits," Economics Letters, Elsevier, vol. 191(C).
    58. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Alexandros Garefalakis & Nikolaos Sariannidis, 2020. "Greek sovereign crisis and European exchange rates: effects of news releases and their providers," Annals of Operations Research, Springer, vol. 294(1), pages 515-536, November.
    59. 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.
    60. Guillaume Coqueret & Tony Guida, 2020. "Training trees on tails with applications to portfolio choice," Annals of Operations Research, Springer, vol. 288(1), pages 181-221, May.
    61. Dobrynskaya, Victoria, 2019. "Avoiding momentum crashes: Dynamic momentum and contrarian trading," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    62. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, December.
    63. Vitor Azevedo & Georg Sebastian Kaiser & Sebastian Mueller, 2023. "Stock market anomalies and machine learning across the globe," Journal of Asset Management, Palgrave Macmillan, vol. 24(5), pages 419-441, September.
    64. Jangkoo Kang & Kyung Yoon Kwon, 2019. "How about selling commodity futures losers?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1489-1514, December.
    65. Weber, Martin & Jacobs, Heiko & Regele, Tobias, 2015. "Expected Skewness and Momentum," CEPR Discussion Papers 10601, C.E.P.R. Discussion Papers.
    66. 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.
    67. Lin, Chaonan & Xia, Chuanxin & Yang, Nien-Tzu & Yang, Sheng-Yung, 2020. "Enhancing momentum profits in the Taiwan Stock Market: The role of extreme absolute strength," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    68. Igor Ferreira Batista Martins & Hedibert Freitas Lopes, 2023. "Stochastic volatility models with skewness selection," Papers 2312.00282, arXiv.org.
    69. Maurice McCourt, 2022. "Permanent private equity: Market performance and transactions," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(2), pages 339-383, June.
    70. Eichel, Ron, 2021. "Momentum in real economy and industry stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    71. Hongwei Chuang, 2020. "The impacts of institutional ownership on stock returns," Empirical Economics, Springer, vol. 58(2), pages 507-533, February.
    72. Zhenya Liu & Shanglin Lu & Shixuan Wang, 2021. "Asymmetry, tail risk and time series momentum," Post-Print hal-03511436, HAL.
    73. Julio Lobao & Joao Meira Fernandes, 2017. "The 52-Week High and Momentum Investing: Implications for Asset Pricing Models," Annals of Economics and Finance, Society for AEF, vol. 18(2), pages 349-376, November.
    74. Christopher G. Lamoureux & Huacheng Zhang, 2021. "An Empirical Assessment of Characteristics and Optimal Portfolios," Papers 2104.12975, arXiv.org, revised Feb 2024.
    75. Patton, Andrew J. & Weller, Brian M., 2020. "What you see is not what you get: The costs of trading market anomalies," Journal of Financial Economics, Elsevier, vol. 137(2), pages 515-549.
    76. Benjamin Chabot & Eric Ghysels & Ravi Jagannathan, 2014. "Momentum Trading, Return Chasing and Predictable Crashes," Working Paper Series WP-2014-27, Federal Reserve Bank of Chicago.
    77. Mehdi Zolfaghari & Bahram Sahabi, 2021. "The impact of oil price and exchange rate on momentum strategy profits in stock market: evidence from oil-rich developing countries," Review of Managerial Science, Springer, vol. 15(7), pages 1981-2023, October.
    78. Francisco Peñaranda & Liuren Wu, 2022. "Targets, Predictability, and Performance," Management Science, INFORMS, vol. 68(2), pages 1537-1555, February.
    79. Alex YiHou Huang & Ming-Che Hu & Quang Thai Truong, 2021. "Asymmetrical impacts from overnight returns on stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 849-889, April.
    80. Kim, Hyuksoo & Kim, Saejoon, 2022. "Managing downside risk of low-risk anomaly portfolios," Finance Research Letters, Elsevier, vol. 46(PB).
    81. 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.
    82. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    83. Julián R. Siri & Juan A. Serur & José P. Dapena, 2017. "Testing momentum effectfor the US market: From equity to option strategies," CEMA Working Papers: Serie Documentos de Trabajo. 621, Universidad del CEMA.
    84. Alan Moreira & Tyler Muir, 2016. "Volatility Managed Portfolios," NBER Working Papers 22208, National Bureau of Economic Research, Inc.
    85. Zhida Yin & Jilin Jiang & Zongxin Qian, 2023. "How does the volatility‐timing strategy perform in mutual funds portfolios," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 87-102, March.
    86. 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.
    87. Yamani, Ehab, 2021. "Can technical trading beat the foreign exchange market in times of crisis?," Global Finance Journal, Elsevier, vol. 48(C).
    88. 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.
    89. Zhang, Wei & Wang, Pengfei & Li, Yi, 2021. "Bond intraday momentum," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    90. Khurshid Ahmad & JingGuang Han & Elaine Hutson & Colm Kearney & Sha Liu, 2016. "Media-expressed negative tone and firm-level stock returns," Open Access publications 10197/8208, Research Repository, University College Dublin.
    91. 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.
    92. Dong, Liang & Dai, Yiqing & Haque, Tariq & Kot, Hung Wan & Yamada, Takeshi, 2022. "Coskewness and reversal of momentum returns: The US and international evidence," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 241-264.
    93. Dupuy, Philippe, 2021. "Risk-adjusted return managed carry trade," Journal of Banking & Finance, Elsevier, vol. 129(C).
    94. 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.
    95. Ruenzi, Stefan & Weigert, Florian, 2017. "Momentum and Crash Sensitivity," Working Papers on Finance 1801, University of St. Gallen, School of Finance.
    96. Azevedo, Vitor, 2023. "Analysts’ underreaction and momentum strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    97. Herrmann, Ulf & Rohleder, Martin & Scholz, Hendrik, 2016. "Does style-shifting activity predict performance? Evidence from equity mutual funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 112-130.
    98. Thesmar , David & Bouchaud , Jean-Philippe & Stefano , Ciliberti & Landier , Augustin & Simon , Guillaume, 2016. "The Excess Returns of 'Quality' Stocks: A Behavioral Anomaly," HEC Research Papers Series 1134, HEC Paris.
    99. 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.
    100. 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.
    101. Maio, Paulo & Philip, Dennis, 2018. "Economic activity and momentum profits: Further evidence," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 466-482.
    102. 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.
    103. 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.
    104. 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.
    105. Panahidargahloo, Akram, 2020. "Positional momentum and liquidity management; a bivariate rank approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    106. Varvara V. Nazarova & Sergei I. Leshchev, 2023. "Study of the Momentum Effect in the Price Dynamics of Highly Liquid Shares on the Russian Securities Market," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 58-73, February.
    107. Mario Cerrato & Zhekai Zhang, 2019. "Can we predict currency momentum crashes?," Working Papers 2019_12, Business School - Economics, University of Glasgow.
    108. Eero J. Pätäri & Timo H. Leivo & Janne Hulkkonen & J. V. Samuli Honkapuro, 2018. "Enhancement of value investing strategies based on financial statement variables: the German evidence," Review of Quantitative Finance and Accounting, Springer, vol. 51(3), pages 813-845, October.
    109. Mario Cerrato & Danyang Li & Zhekai Zhang, 2020. "Factor Investing and forex Portfolio Management," Working Papers 2020_01, Business School - Economics, University of Glasgow.
    110. 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.
    111. Yilmaz Yildiz & Mehmet Baha Karan, 2020. "Environmental policies, national culture, and stock price crash risk: Evidence from renewable energy firms," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2374-2391, September.
    112. Chang, Rosita P. & Ko, Kuan-Cheng & Nakano, Shinji & Ghon Rhee, S., 2018. "Residual momentum in Japan," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 283-299.
    113. Tim A. Herberger & Matthias Horn & Andreas Oehler, 2020. "Are intraday reversal and momentum trading strategies feasible? An analysis for German blue chip stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 179-197, June.
    114. Chen, Li-Wen & Yu, Hsin-Yi & Wang, Wen-Kai, 2018. "Evolution of historical prices in momentum investing," Journal of Financial Markets, Elsevier, vol. 37(C), pages 120-135.
    115. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Smoothing volatility targeting," Papers 2212.07288, arXiv.org.
    116. Federico Nucera & Björn Uhl, 2022. "The impact of volatility scaling on factor portfolio performance and factor timing," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 522-533, October.
    117. Flögel, Volker & Schlag, Christian & Zunft, Claudia, 2022. "Momentum-Managed Equity Factors," Journal of Banking & Finance, Elsevier, vol. 137(C).
    118. Marie Briere & Ariane Szafarz, 2015. "Factor-Based v. Industry-Based Asset Allocation: The Contest," Working Papers CEB 15-035, ULB -- Universite Libre de Bruxelles.
    119. 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.
    120. Lin, Chaonan & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2022. "Does the momentum gap explain momentum in Taiwan?," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    121. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the time-varying dynamics of stock and commodity momentum returns," Finance Research Letters, Elsevier, vol. 46(PB).
    122. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
    123. Vitor Azevedo & Christopher Hoegner, 2023. "Enhancing stock market anomalies with machine learning," Review of Quantitative Finance and Accounting, Springer, vol. 60(1), pages 195-230, January.
    124. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch & Seong-Min Yoon, 2020. "OPEC News and Jumps in the Oil Market," Working Papers 202053, University of Pretoria, Department of Economics.
    125. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    126. Jorge M. Uribe, 2018. "“Scaling Down Downside Risk with Inter-Quantile Semivariances”," IREA Working Papers 201826, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
    127. Jank, Stephan, 2015. "Specialized human capital, unemployment risk, and the value premium," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113214, Verein für Socialpolitik / German Economic Association.
    128. Lin, Yu En & Chu, Chien Chi & Omura, Akihiro & Li, Bin & Roca, Eduardo, 2020. "Arbitrage risk and the cross-section of stock returns: Evidence from China," Emerging Markets Review, Elsevier, vol. 43(C).
    129. Bryan Lim & Stefan Zohren & Stephen Roberts, 2019. "Enhancing Time Series Momentum Strategies Using Deep Neural Networks," Papers 1904.04912, arXiv.org, revised Sep 2020.
    130. 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.
    131. Yasuhiro Iwanaga & Ryuta Sakemoto, 2023. "Commodity momentum decomposition," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(2), pages 198-216, February.
    132. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    133. Jürgen Vandenbroucke, 2017. "The role of correlation in risk profile portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 18(2), pages 144-153, March.
    134. 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.
    135. 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.
    136. Manuel Ammann & Sebastian Fischer & Florian Weigert, 2018. "Risk Factor Exposure Variation and Mutual Fund Performance," Working Papers on Finance 1817, University of St. Gallen, School of Finance, revised Nov 2018.
    137. 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.
    138. 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.
    139. van Zundert, Jeroen, 2018. "Empirical studies on the cross-section of corporate bond and stock markets," Other publications TiSEM 338205fc-a031-4e06-a636-9, Tilburg University, School of Economics and Management.
    140. Xiong, Haifang & Yang, Gaofei & Wang, Zhiqiang, 2022. "Factor portfolio and target volatility management: An analysis of portfolio performance in the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 493-517.
    141. Li, Yan & Liang, Chao & L.D. Huynh, Toan, 2022. "A new momentum measurement in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    142. Elie Bouri & Konstantinos Gkillas & Rangan Gupta, 2020. "Trade uncertainties and the hedging abilities of Bitcoin," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(3), September.
    143. 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.
    144. Y. Lemp'eri`ere & C. Deremble & P. Seager & M. Potters & J. P. Bouchaud, 2014. "Two centuries of trend following," Papers 1404.3274, arXiv.org.
    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. Yao Zheng & Peihwang Wei & Eric Osmer, 2022. "The relation between earnings and price momentum: Does it vary across regimes?," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1145-1213, April.
    147. Andrea J. Heuson & Mark C. Hutchinson & Alok Kumar, 2020. "Predicting hedge fund performance when fund returns are skewed," Financial Management, Financial Management Association International, vol. 49(4), pages 877-896, December.
    148. Theissen, Erik & Zimmermann, Lukas, 2020. "Do contented customers make shareholders wealthy? Implications of intangibles for security pricing," CFR Working Papers 20-12, University of Cologne, Centre for Financial Research (CFR).
    149. Jorge M. Uribe & Montserrat Guillen, 2020. "Generalized Market Uncertainty Measurement in European Stock Markets in Real Time," Mathematics, MDPI, vol. 8(12), pages 1-11, December.
    150. Martin H. Schmidt, 2017. "Trading strategies based on past returns: evidence from Germany," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(2), pages 201-256, May.
    151. Theissen, Erik & Yilanci, Can, 2020. "Momentum? What Momentum?," CFR Working Papers 20-09, University of Cologne, Centre for Financial Research (CFR).
    152. Fangming Xu & Huainan Zhao & Liyi Zheng, 2022. "Investment momentum: A two‐dimensional behavioural strategy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1191-1207, January.
    153. Bohl, Martin T. & Czaja, Marc-Gregor & Kaufmann, Philipp, 2016. "Momentum profits, market cycles, and rebounds: Evidence from Germany," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 139-159.
    154. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2021. "Return signal momentum," Journal of Banking & Finance, Elsevier, vol. 124(C).
    155. Blitz, David & Hanauer, Matthias X. & Vidojevic, Milan, 2020. "The idiosyncratic momentum anomaly," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 932-957.
    156. Yang Gao & Henry Leung & Stephen Satchell, 2018. "A critique of momentum strategies," Journal of Asset Management, Palgrave Macmillan, vol. 19(5), pages 341-350, September.
    157. Fabian Hollstein & Marcel Prokopczuk, 2023. "Managing the Market Portfolio," Management Science, INFORMS, vol. 69(6), pages 3675-3696, June.
    158. William Goetzmann & Simon Huang, 2015. "Momentum in Imperial Russia," NBER Working Papers 21700, National Bureau of Economic Research, Inc.
    159. Qi Xu & Ying Wang, 2021. "Managing volatility in commodity momentum," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 758-782, May.
    160. Dahlquist, Magnus & Hasseltoft, Henrik, 2020. "Economic momentum and currency returns," Journal of Financial Economics, Elsevier, vol. 136(1), pages 152-167.
    161. Assaf Eisdorfer & Efdal Ulas Misirli, 2020. "Distressed Stocks in Distressed Times," Management Science, INFORMS, vol. 66(6), pages 2452-2473, June.
    162. Klaus Grobys & Sami Vähämaa, 2020. "Another look at value and momentum: volatility spillovers," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1459-1479, November.
    163. Chulwoo Han, 2022. "Bimodal Characteristic Returns and Predictability Enhancement via Machine Learning," Management Science, INFORMS, vol. 68(10), pages 7701-7741, October.
    164. Zhaobo Zhu & Licheng Sun & Min Chen, 2023. "Fundamental strength and the 52-week high anchoring effect," Review of Quantitative Finance and Accounting, Springer, vol. 60(4), pages 1515-1542, May.
    165. Chen, Tsung-Yu & Chou, Pin-Huang & Yang, Nien-Tzu, 2020. "Momentum and reversals: Are they really separate phenomena?," Finance Research Letters, Elsevier, vol. 32(C).
    166. Jian Wang & Yanhuang Huang & Hongrui Feng & Xingjian Li & Shu Yan, 2023. "CEO incentive compensation and stock price momentum," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(S1), pages 975-1028, April.
    167. Kerstin Lamert & Benjamin R. Auer & Ralf Wunderlich, 2023. "Discretization of continuous-time arbitrage strategies in financial markets with fractional Brownian motion," Papers 2311.15635, arXiv.org.
    168. Kim, Byungoh & Suh, Sangwon, 2018. "Sentiment-based momentum strategy," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 52-68.
    169. Sadaqat, Mohsin & Butt, Hilal Anwar, 2023. "Stop-loss rules and momentum payoffs in cryptocurrencies," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    170. Xiaoyue Chen & Bin Li & Andrew C. Worthington, 2022. "Realised volatility and industry momentum returns," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    171. Teplova, Tamara & Tomtosov, Aleksandr, 2021. "Can high trading volume and volatility switch boost momentum to show greater inefficiency and avoid crashes in emerging markets? The economic relationship in factor investing in emerging markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 210-223.
    172. Hong‐Yi Chen & Pin‐Huang Chou & Chia‐Hsun Hsieh, 2018. "Persistency of the momentum effect," European Financial Management, European Financial Management Association, vol. 24(5), pages 856-892, November.
    173. Le, Trung H., 2021. "International portfolio allocation: The role of conditional higher moments," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 33-57.
    174. Hilal Anwar Butt & Nader Shahzad Virk, 2022. "Momentum crashes and variations to market liquidity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1899-1911, April.
    175. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    176. Wang, Feifei & Yan, Xuemin Sterling, 2021. "Downside risk and the performance of volatility-managed portfolios," Journal of Banking & Finance, Elsevier, vol. 131(C).
    177. 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).
    178. Ammann, Manuel & Fischer, Sebastian & Weigert, Florian, 2020. "Factor exposure variation and mutual fund performance," CFR Working Papers 20-06, University of Cologne, Centre for Financial Research (CFR).
    179. Chen, Zhanhui & Yang, Bowen, 2019. "In search of preference shock risks: Evidence from longevity risks and momentum profits," Journal of Financial Economics, Elsevier, vol. 133(1), pages 225-249.
    180. Guillaume Coqueret & Tony Guida, 2020. "Training trees on tails with applications to portfolio choice," Post-Print hal-04144665, HAL.
    181. Ming‐Yu Liu, 2019. "Improving momentum strategies using residual returns and option‐implied information," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(4), pages 499-521, April.
    182. 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.
    183. Vishaal Baulkaran & Pawan Jain & Mark Sunderman, 2019. "Housing “Beta”: Common Risk Factor in Returns of Stocks," The Journal of Real Estate Finance and Economics, Springer, vol. 58(3), pages 438-456, April.
    184. Robert Novy-Marx, 2015. "Fundamentally, Momentum is Fundamental Momentum," NBER Working Papers 20984, National Bureau of Economic Research, Inc.
    185. Friedrich-Carl Franz & Tobias Regele, 2016. "Beating the DAX, MDAX, and SDAX: investment strategies in Germany," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(2), pages 161-204, May.
    186. Guo, Xu & Lin, Hai & Wu, Chunchi & Zhou, Guofu, 2022. "Predictive information in corporate bond yields," Journal of Financial Markets, Elsevier, vol. 59(PB).
    187. Angelidis, Timotheos & Tessaromatis, Nikolaos, 2023. "The disappearing profitability of volatility-managed equity factors," Journal of Financial Markets, Elsevier, vol. 65(C).
    188. Enoch Cheng & Clemens C. Struck, 2019. "Time-Series Momentum: A Monte-Carlo Approach," Working Papers 201906, School of Economics, University College Dublin.
    189. Dupuy, Philippe & James, Jessica & Marsh, Ian W., 2021. "Attractive and non-attractive currencies," Journal of International Money and Finance, Elsevier, vol. 110(C).
    190. Keyi Zhang & Ramazan Gençay, 2019. "Mutual Fund Performance In Developing And Advanced World Networks," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(02), pages 399-421, March.
    191. Haixiang Yao & Xun Li & Zhifeng Hao & Yong Li, 2016. "Dynamic asset–liability management in a Markov market with stochastic cash flows," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1575-1597, October.
    192. 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.
    193. Hyuna Ham & Hoon Cho & Hyeongjun Kim & Doojin Ryu, 2019. "Time‐series momentum in China's commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1515-1528, December.
    194. Ran, Rong & Li, Cheng & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2022. "State-dependent psychological anchors and momentum," Finance Research Letters, Elsevier, vol. 46(PB).
    195. Barroso, Pedro & Boons, Martijn & Karehnke, Paul, 2021. "Time-varying state variable risk premia in the ICAPM," Journal of Financial Economics, Elsevier, vol. 139(2), pages 428-451.
    196. Tang, Tao & Wang, Yanchen, 2022. "Liquidity Shocks, Price Volatilities, and Risk-managed Strategy: Evidence from Bitcoin and Beyond," Journal of Multinational Financial Management, Elsevier, vol. 64(C).
    197. Kobinger, Sonja & Bornholt, Graham & Malin, Mirela, 2020. "Long-term time series reversal: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    198. Blanco, Ivan & De Jesus, Miguel & Remesal, Alvaro, 2023. "Overlapping momentum portfolios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 1-22.
    199. Nick Inglis & Bruce Vanstone & Tobias Hahn, 2019. "Modelling momentum winner/loser asymmetry: the sources of winner and loser returns in the ASX200 and S&P500," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(S1), pages 657-684, April.
    200. Victoria Dobrynskaya, 2017. "Dynamic Momentum and Contrarian Trading," HSE Working papers WP BRP 61/FE/2017, National Research University Higher School of Economics.
    201. Eriksen, Jonas N., 2019. "Cross-sectional return dispersion and currency momentum," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 91-108.
    202. Cai, Haidong & Jiang, Ying & Liu, Xiaoquan, 2022. "Investor attention, aggregate limit-hits, and stock returns," International Review of Financial Analysis, Elsevier, vol. 83(C).
    203. 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).
    204. Joel Ong & Dorien Herremans, 2023. "Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning," Papers 2306.13661, arXiv.org.
    205. Sangwon Suh, 2021. "A Filtering Strategy for Improving Charateristics-Based Portfolios," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 46(2), pages 119-153, June.
    206. Nick Taylor, 2023. "The Determinants of Volatility Timing Performance," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1228-1257.
    207. Marie Briere & Ariane Szafarz, 2018. "Factors and Sectors in Asset Allocation: Stronger Together?," Working Papers CEB 18-016, ULB -- Universite Libre de Bruxelles.
    208. Jiaqi Guo & Peng Li & Youwei Li, 2022. "What Can Explain Momentum? Evidence from Decomposition," Management Science, INFORMS, vol. 68(8), pages 6184-6218, August.
    209. Jin Zhang & Yuxiu Zhang & Yongqi Dong, 2021. "A New Momentum Strategy Based on Chinese Securities Market," International Journal of Business and Management, Canadian Center of Science and Education, vol. 14(12), pages 1-90, July.
    210. Boguth, Oliver & Simutin, Mikhail, 2018. "Leverage constraints and asset prices: Insights from mutual fund risk taking," Journal of Financial Economics, Elsevier, vol. 127(2), pages 325-341.
    211. Butt, Hilal Anwar & Kolari, James W. & Sadaqat, Mohsin, 2021. "Revisiting momentum profits in emerging markets," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    212. 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.
    213. Kim, Abby Y. & Tse, Yiuman & Wald, John K., 2016. "Time series momentum and volatility scaling," Journal of Financial Markets, Elsevier, vol. 30(C), pages 103-124.
    214. Tsung‐Yu Chen & Guan‐Ying Huang & Zhen‐Xing Wu, 2022. "Overreaction‐based momentum in the real estate investment trust market," International Review of Finance, International Review of Finance Ltd., vol. 22(3), pages 453-471, September.
    215. Fousseni Chabi-Yo & Markus Huggenberger & Florian Weigert, 2019. "Multivariate Crash Risk," Working Papers on Finance 1901, University of St. Gallen, School of Finance.
    216. Sirio Aramonte & Mohammad Jahan-Parvar & Samuel Rosen & John W. Schindler, 2017. "Firm-Specific Risk-Neutral Distributions : The Role of CDS Spreads," International Finance Discussion Papers 1212, Board of Governors of the Federal Reserve System (U.S.).
    217. Hanauer, Matthias X. & Windmüller, Steffen, 2023. "Enhanced momentum strategies," Journal of Banking & Finance, Elsevier, vol. 148(C).

  2. Maio, Paulo & Santa-Clara, Pedro, 2015. "Dividend Yields, Dividend Growth, and Return Predictability in the Cross Section of Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(1-2), pages 33-60, April.

    Cited by:

    1. Pham, Quynh Thi Thuy, 2021. "Stock Return Predictability: Evidence Across US Industries," Finance Research Letters, Elsevier, vol. 38(C).
    2. Ricardo De la O & Sean Myers, 2018. "Subjective Cash Flows and Discount Rates," 2018 Meeting Papers 291, Society for Economic Dynamics.
    3. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    4. Davide Pettenuzzo & Riccardo Sabbatucci & Allan Timmermann, 2018. "High-frequency Cash Flow Dynamics," Working Papers 120, Brandeis University, Department of Economics and International Business School.
    5. Maio, Paulo, 2016. "Cross-sectional return dispersion and the equity premium," Journal of Financial Markets, Elsevier, vol. 29(C), pages 87-109.
    6. 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.
    7. Kragt, Jac, 2018. "This time it's dividend," Other publications TiSEM 8959787b-5bef-40bd-ae17-9, Tilburg University, School of Economics and Management.
    8. Malamud, Semyon & Vilkov, Grigory, 2018. "Non-myopic betas," Journal of Financial Economics, Elsevier, vol. 129(2), pages 357-381.
    9. Jiang, Fuxiu & Cai, Xinni & Jiang, Zhan & Nofsinger, John R., 2019. "Multiple large shareholders and dividends: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    10. 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.
    11. Lan, Chunhua & Doan, Bao, 2022. "Stock price movements: Evidence from global equity markets," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 123-143.
    12. Shi, Jinyan & Yu, Conghui & Liu, Xiangkun & Li, Yanxi, 2020. "Predicting firm stock returns with customer stock returns: Moderating effects of customer characteristics," Research in International Business and Finance, Elsevier, vol. 54(C).
    13. Khurshid Ahmad & JingGuang Han & Elaine Hutson & Colm Kearney & Sha Liu, 2016. "Media-expressed negative tone and firm-level stock returns," Open Access publications 10197/8208, Research Repository, University College Dublin.
    14. 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.
    15. 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.
    16. Tetsuya Adachi & Takashi Asano & Tatsushi Okuda, 2016. "Simultaneous Estimation of Cost of Equity and Expected Earnings of Individual Firms with the Residual Income Model," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 34, pages 1-38, November.
    17. Maio, Paulo & Xu, Danielle, 2020. "Cash-flow or return predictability at long horizons? The case of earnings yield," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 172-192.
    18. Yun, Jaeho, 2020. "A re-examination of the predictability of stock returns and cash flows via the decomposition of VIX," Economics Letters, Elsevier, vol. 186(C).
    19. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    20. Golez, Benjamin & Koudijs, Peter, 2018. "Four centuries of return predictability," Journal of Financial Economics, Elsevier, vol. 127(2), pages 248-263.
    21. Møller, Stig V. & Sander, Magnus, 2017. "Dividends, earnings, and predictability," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 153-163.

  3. Barroso, Pedro & Santa-Clara, Pedro, 2015. "Beyond the Carry Trade: Optimal Currency Portfolios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(5), pages 1037-1056, October.

    Cited by:

    1. Yamani, Ehab, 2019. "Diversification role of currency momentum for carry trade: Evidence from financial crises," Journal of Multinational Financial Management, Elsevier, vol. 49(C), pages 1-19.
    2. Della Corte, Pasquale & Ramadorai, Tarun & Sarno, Lucio, 2016. "Volatility risk premia and exchange rate predictability," Journal of Financial Economics, Elsevier, vol. 120(1), pages 21-40.
    3. Pasquale Della Corte & Lucio Sarno & Maik Schmeling & Christian Wagner, 2022. "Exchange Rates and Sovereign Risk," Management Science, INFORMS, vol. 68(8), pages 5591-5617, August.
    4. David R. Haab & Thomas Nitschka, 2020. "Carry trade and forward premium puzzle from the perspective of a safe‐haven currency," Review of International Economics, Wiley Blackwell, vol. 28(2), pages 376-394, May.
    5. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2022. "The time-varying risk price of currency portfolios," Journal of International Money and Finance, Elsevier, vol. 124(C).
    6. Laborda, Ricardo & Laborda, Juan, 2017. "Can tree-structured classifiers add value to the investor?," Finance Research Letters, Elsevier, vol. 22(C), pages 211-226.
    7. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    8. Colacito, Riccardo & Riddiough, Steven J. & Sarno, Lucio, 2020. "Business cycles and currency returns," Journal of Financial Economics, Elsevier, vol. 137(3), pages 659-678.
    9. 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.
    10. Mitchener, Kris James & Pina, Gonçalo, 2020. "Pegxit pressure," Journal of International Money and Finance, Elsevier, vol. 107(C).
    11. Andrew Clare & James Seaton & Peter N. Smith & Stephen Thomas, 2015. "Carry and Trend Following Returns in the Foreign Exchange Market," Discussion Papers 15/07, Department of Economics, University of York.
    12. Sakemoto, Ryuta, 2018. "Do precious and industrial metals act as hedges and safe havens for currency portfolios?," Finance Research Letters, Elsevier, vol. 24(C), pages 256-262.
    13. Pedro Barroso & Jurij-Andrei Reichenecker & Marco J. Menichetti, 2022. "Hedging with an Edge: Parametric Currency Overlay," Management Science, INFORMS, vol. 68(1), pages 669-689, January.
    14. Ricardo Laborda & Ramiro Losada, 2017. "Why is investors'mutual fund market allocation far from the optimum?," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    15. Atanasov, Victoria & Nitschka, Thomas, 2014. "Currency excess returns and global downside market risk," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 268-285.
    16. Vanja Piljak & Laurens Swinkels, 2017. "Fundamental indexation for developed, emerging, and frontier government bond markets," Journal of Asset Management, Palgrave Macmillan, vol. 18(5), pages 405-420, September.
    17. Charles W. Calomiris & Harry Mamaysky, 2019. "Monetary Policy and Exchange Rate Returns: Time-Varying Risk Regimes," NBER Working Papers 25714, National Bureau of Economic Research, Inc.
    18. Fuertes, Ana-Maria & Zhao, Nan, 2023. "A Bayesian perspective on commodity style integration," Journal of Commodity Markets, Elsevier, vol. 30(C).
    19. Choi, Jin Ho & Suh, Sangwon, 2022. "Conditionally-hedged currency carry trades," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    20. Geert Bekaert & George Panayotov, 2019. "Good Carry, Bad Carry," NBER Working Papers 25420, National Bureau of Economic Research, Inc.
    21. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova, 2018. "Exchange rate forecasting and the performance of currency portfolios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 519-540, August.
    22. Anna Boldizsár & Zalán Kocsis & Zsuzsa Nagy-Kékesi & Gábor Sztanó, 2020. "FX Forward Market in Hungary: General Characteristics and Impact of the COVID Crisis," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 19(3), pages 5-51.
    23. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joelle, 2021. "The risk premia of energy futures," Energy Economics, Elsevier, vol. 102(C).
    24. José Renato Haas Ornelas, 2017. "Expected Currency Returns and Volatility Risk Premia," Working Papers Series 454, Central Bank of Brazil, Research Department.
    25. Fuertes, Ana-Maria & Zhao, Nan, 2022. "A Bayesian Perspective on Commodity Style Integration," MPRA Paper 117831, University Library of Munich, Germany, revised 2023.
    26. Hutchinson, Mark C. & Kyziropoulos, Panagiotis E. & O’Brien, John & O’Reilly, Philip & Sharma, Tripti, 2022. "Technical trading rule profitability in currencies: It’s all about momentum," Research in International Business and Finance, Elsevier, vol. 63(C).
    27. 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.
    28. Sarno, Lucio & Menkhoff, Lukas & Schmeling, Maik & Schrimpf, Paul, 2016. "Currency Value," CEPR Discussion Papers 11324, C.E.P.R. Discussion Papers.
    29. Jeremy Graveline & Irina Zviadadze & Mikhail Chernov, 2012. "Crash Risk in Currency Returns," 2012 Meeting Papers 753, Society for Economic Dynamics.
    30. Martin, Ian & Kremens, Lukas, 2017. "The Quanto Theory of Exchange Rates," CEPR Discussion Papers 11970, C.E.P.R. Discussion Papers.
    31. 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.
    32. Alla Petukhina & Simon Trimborn & Wolfgang Karl Härdle & Hermann Elendner, 2021. "Investing with cryptocurrencies – evaluating their potential for portfolio allocation strategies," Quantitative Finance, Taylor & Francis Journals, vol. 21(11), pages 1825-1853, November.
    33. Fullwood, Jonathan & James, Jessica & Marsh, Ian W., 2021. "Volatility and the cross-section of returns on FX options," Journal of Financial Economics, Elsevier, vol. 141(3), pages 1262-1284.
    34. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    35. Byrne, Joseph P. & Sakemoto, Ryuta, 2021. "The conditional volatility premium on currency portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    36. 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).
    37. Harris, Richard D.F. & Shen, Jian & Yilmaz, Fatih, 2022. "Maximally predictable currency portfolios," Journal of International Money and Finance, Elsevier, vol. 128(C).
    38. Joseph, Byrne & Sakemoto, Ryuta, 2020. "The Conditional Risk and Return Trade-Off on Currency Portfolios," MPRA Paper 99497, University Library of Munich, Germany.
    39. Rubaszek, Michał & Beckmann, Joscha & Ca' Zorzi, Michele & Kwas, Marek, 2022. "Boosting carry with equilibrium exchange rate estimates," Working Paper Series 2731, European Central Bank.
    40. Schüssler, Rainer & Beckmann, Joscha & Koop, Gary & Korobilis, Dimitris, 2018. "Exchange rate predictability and dynamic Bayesian learning," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181523, Verein für Socialpolitik / German Economic Association.
    41. Mulder, Arjen & Tims, Ben, 2018. "Conditioning carry trades: Less risk, more return," Journal of International Money and Finance, Elsevier, vol. 85(C), pages 1-19.
    42. Cenedese, Gino, 2015. "Safe haven currencies: a portfolio perspective," Bank of England working papers 533, Bank of England.
    43. Chen, Chih-Nan & Lin, Chien-Hsiu, 2020. "The sources of pricing factors underlying the cross-section of currency returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 250-265.
    44. Dupuy, Philippe, 2021. "Risk-adjusted return managed carry trade," Journal of Banking & Finance, Elsevier, vol. 129(C).
    45. Choi, Jae Hoon & Song, Seongho, 2022. "Revisiting the PPP puzzle: Nominal exchange rate rigidity and region of inaction," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    46. Zhang, Shaojun, 2022. "Dissecting currency momentum," Journal of Financial Economics, Elsevier, vol. 144(1), pages 154-173.
    47. Chandrinos, Spyros K. & Lagaros, Nikos D., 2018. "Construction of currency portfolios by means of an optimized investment strategy," Operations Research Perspectives, Elsevier, vol. 5(C), pages 32-44.
    48. Mario Cerrato & Danyang Li & Zhekai Zhang, 2020. "Factor Investing and forex Portfolio Management," Working Papers 2020_01, Business School - Economics, University of Glasgow.
    49. Steven Riddiough & Lucio Sarno & Pasquale Della Corte, 2015. "Currency Premia and Global Imbalances," 2015 Meeting Papers 1215, Society for Economic Dynamics.
    50. Choi, Jin Ho & Suh, Sangwon, 2021. "A filtered currency carry trade," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    51. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
    52. Joenväärä, Juha & Kauppila, Mikko & Kahra, Hannu, 2021. "Hedge fund portfolio selection with fund characteristics," Journal of Banking & Finance, Elsevier, vol. 132(C).
    53. Yung, Julieta, 2021. "Can interest rate factors explain exchange rate fluctuations?," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 34-56.
    54. Li, Danyang & Shi, Yukun & Xu, Liao & Xu, Yahua & Zhao, Yang, 2022. "Dynamic asymmetric dependence and portfolio management in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 48(C).
    55. Walter Bazán-Palomino & Diego Winkelried, 2021. "FX markets’ reactions to COVID-19: Are they different?," International Economics, CEPII research center, issue 167, pages 50-58.
    56. Lee, Namhoon & Choi, Wonseok & Pae, Yuntaek, 2021. "Market efficiency in foreign exchange market," Economics Letters, Elsevier, vol. 205(C).
    57. Dahlquist, Magnus & Hasseltoft, Henrik, 2020. "Economic momentum and currency returns," Journal of Financial Economics, Elsevier, vol. 136(1), pages 152-167.
    58. Opie, Wei & Riddiough, Steven J., 2020. "Global currency hedging with common risk factors," Journal of Financial Economics, Elsevier, vol. 136(3), pages 780-805.
    59. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    60. Raúl Álvarez del Castillo Penna & José Antonio Núñez Mora & Leovardo Mata Mata, 2018. "Foreign Exchange Strategies Performance," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 13(2), pages 195-245, Abril-Jun.
    61. Li, Danyang & Zhang, Zhekai & Cerrato, Mario, 2023. "Factor investing and currency portfolio management," International Review of Financial Analysis, Elsevier, vol. 87(C).
    62. A. Mikhailov Yu. & А. Михайлов Ю., 2018. "Доходность Стратегии Carry Trade // The Yield Of The Carry Trade Strategy," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(3), pages 52-63.
    63. Suh, Sangwon, 2019. "Unexploited currency carry trade profit opportunity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 236-254.
    64. Suk Joon Byun & Bart Frijns & Tai‐Yong Roh, 2018. "A comprehensive look at the return predictability of variance risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(4), pages 425-445, April.
    65. Lukas Mankhoff & Lucio Sarno & Maik Schmeling & Andreas Schrimpf, 2013. "Information flows in foreign exchange markets: dissecting customer currency trades," BIS Working Papers 405, Bank for International Settlements.
    66. Chernov, Mikhail & Graveline, Jeremy & Zviadadze, Irina, 2012. "Sources of Risk in Currency Returns," CEPR Discussion Papers 8745, C.E.P.R. Discussion Papers.
    67. Sakemoto, Ryuta, 2021. "Economic Evaluation of Cryptocurrency Investment," MPRA Paper 108283, University Library of Munich, Germany.
    68. Baltussen, Guido & Swinkels, Laurens & Van Vliet, Pim, 2021. "Global factor premiums," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1128-1154.
    69. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J. & Uppal, Raman, 2017. "A Portfolio Perspective on the Multitude of Firm Characteristics," CEPR Discussion Papers 12417, C.E.P.R. Discussion Papers.
    70. 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.

  4. 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.

    Cited by:

    1. Wallmeier,, 2016. "Entwicklungslinien in der Portfoliotheorie und im Asset Management," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 70(4), pages 407-422.
    2. de Oliveira Souza, Thiago, 2016. "The size premium and intertemporal risk," Discussion Papers on Economics 3/2016, University of Southern Denmark, Department of Economics.
    3. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2022. "The time-varying risk price of currency portfolios," Journal of International Money and Finance, Elsevier, vol. 124(C).
    4. Javier Rojo-Suárez & Ana Belén Alonso-Conde, 2020. "Impact of consumer confidence on the expected returns of the Tokyo Stock Exchange: A comparative analysis of consumption and production-based asset pricing models," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
    5. Sakemoto, Ryuta, 2019. "Currency carry trades and the conditional factor model," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 198-208.
    6. Li, Xiao-Ming, 2017. "New evidence on economic policy uncertainty and equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 46(PA), pages 41-56.
    7. Mikael C. Bergbrant & Patrick J. Kelly, 2015. "Macroeconomic Expectations and the Size, Value and Momentum Factors," Working Papers w0214, New Economic School (NES).
    8. Maximilian Renz & Olaf Stotz, 2021. "A macroeconomic hedge portfolio and the cross section of stock returns," Review of Financial Economics, John Wiley & Sons, vol. 39(1), pages 73-94, January.
    9. Dunbar, Kwamie, 2021. "Pricing the hedging factor in the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    10. Lin, Qi, 2022. "Understanding idiosyncratic momentum in the Chinese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    11. Yuming Li, 2017. "Risks and rewards for momentum and reversal portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 289-315, August.
    12. 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).
    13. Maio, Paulo, 2013. "Return decomposition and the Intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4958-4972.
    14. Esben Hedegaard & Robert J. Hodrick, 2014. "Measuring the Risk-Return Tradeoff with Time-Varying Conditional Covariances," NBER Working Papers 20245, National Bureau of Economic Research, Inc.
    15. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    16. Sy, Oumar & Zaman, Ashraf Al, 2020. "Is the presidential premium spurious?," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 94-104.
    17. Martijn Boons & Frans de Roon & Fernando M. Duarte & Marta Szymanowska, 2013. "Time-Varying Inflation Risk and Stock Returns," Staff Reports 621, Federal Reserve Bank of New York.
    18. Gagnon, Marie-Hélène & Gimet, Céline, 2013. "The impacts of standard monetary and budgetary policies on liquidity and financial markets: International evidence from the credit freeze crisis," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4599-4614.
    19. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    20. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
    21. Kang, Hankil & Ryu, Doojin, 2019. "Information in mispricing factors for future investment opportunities," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 657-668.
    22. Jangkoo Kang & Kyung Yoon Kwon, 2020. "Can commodity futures risk factors predict economic growth?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(12), pages 1825-1860, December.
    23. Pintor, Gabor, 2016. "The macroeconomic shock with the highest price of risk," LSE Research Online Documents on Economics 86225, London School of Economics and Political Science, LSE Library.
    24. Jangkoo Kang & Kyung Yoon Kwon, 2019. "How about selling commodity futures losers?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1489-1514, December.
    25. Shi, Qi & Li, Bin, 2019. "Evaluating alternative methods of asset pricing based on the overall magnitude of pricing errors," Finance Research Letters, Elsevier, vol. 29(C), pages 125-128.
    26. Zhang, Han, 2021. "An inflation-based ICAPM in China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    27. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    28. Rocciolo, Francesco & Gheno, Andrea & Brooks, Chris, 2022. "Explaining abnormal returns in stock markets: An alpha-neutral version of the CAPM," International Review of Financial Analysis, Elsevier, vol. 82(C).
    29. Ripamonti, Alexandre & Silva, Diego & Moreira Neto, Eurico, 2018. "Asset Pricing and Asymmetric Information," MPRA Paper 87403, University Library of Munich, Germany.
    30. Jennie Bai & Turan G. Bali & Quan Wen, 2019. "Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence," NBER Working Papers 25995, National Bureau of Economic Research, Inc.
    31. Byrne, Joseph P. & Sakemoto, Ryuta, 2021. "The conditional volatility premium on currency portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    32. Grammig, Joachim & Jank, Stephan, 2013. "Creative destruction and asset prices," University of Tübingen Working Papers in Business and Economics 61, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    33. 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).
    34. Kroencke, Tim A. & Schindler, Felix & Sebastian, Steffen & Theissen, Erik, 2013. "GDP mimicking portfolios and the cross-section of stock returns," ZEW Discussion Papers 13-026, ZEW - Leibniz Centre for European Economic Research.
    35. Akbari, Amir & Carrieri, Francesca, 2023. "Global risk and market conditions," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 51-70.
    36. Cho, Sungjun, 2013. "New return anomalies and new-Keynesian ICAPM," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 87-106.
    37. Pinter, Gabor, 2016. "The macroeconomic shock with the highest price of risk," Bank of England working papers 616, Bank of England.
    38. Oghenovo A. Obrimah, 2023. "Underpricing of initial public offerings (IPOs) and the credibility of underwriters’ pricing services," SN Business & Economics, Springer, vol. 3(2), pages 1-33, February.
    39. Chichernea, Doina C. & Holder, Anthony D. & Petkevich, Alex, 2015. "Does return dispersion explain the accrual and investment anomalies?," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 133-148.
    40. Qi Shi & Bin Li, 2021. "Forecasting the future state of the economy in the United States: The role of tradable “new” risk factors," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 1039-1046, September.
    41. Faccini, Renato & Matin, Rastin & Skiadopoulos, George, 2023. "Dissecting climate risks: Are they reflected in stock prices?," Journal of Banking & Finance, Elsevier, vol. 155(C).
    42. Maio, Paulo & Philip, Dennis, 2018. "Economic activity and momentum profits: Further evidence," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 466-482.
    43. Park, Sunjin, 2022. "Heterogeneous beliefs in macroeconomic growth prospects and the carry risk premium," Journal of Banking & Finance, Elsevier, vol. 136(C).
    44. Qi Shi & Bin Li & Adrian (Wai Kong) Cheung & Richard Chung, 2017. "Augmenting the intertemporal CAPM with inflation: Further evidence from alternative models," Australian Journal of Management, Australian School of Business, vol. 42(4), pages 653-672, November.
    45. Li, Yuming, 2018. "Investment and profitability versus value and momentum: The price of residual risk," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 1-10.
    46. Lutzenberger, Fabian T., 2014. "The predictability of aggregate returns on commodity futures," Review of Financial Economics, Elsevier, vol. 23(3), pages 120-130.
    47. Gabor Pinter, 2018. "Macroeconomic Shocks and Risk Premia," Discussion Papers 1812, Centre for Macroeconomics (CFM).
    48. Roh, Tai-Yong & Lee, Changjun & Min, Byoung-Kyu, 2019. "Consumption growth predictability and asset prices," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 95-118.
    49. Franke, Benedikt & Müller, Sebastian & Müller, Sonja, 2017. "The q-factors and expected bond returns," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 19-35.
    50. Javier Rojo‐Suárez & Ana Belén Alonso‐Conde & Ricardo Ferrero‐Pozo, 2022. "Liquidity, time‐varying betas and anomalies: Is the high trading activity enhancing the validity of the CAPM in the UK equity market?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 45-60, January.
    51. Maio, Paulo & Xu, Danielle, 2020. "Cash-flow or return predictability at long horizons? The case of earnings yield," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 172-192.
    52. Maio, Paulo & Philip, Dennis, 2015. "Macro variables and the components of stock returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 287-308.
    53. Ryuta Sakemoto, 2022. "Multi‐scale inter‐temporal capital asset pricing model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4298-4317, October.
    54. Boons, Martijn, 2016. "State variables, macroeconomic activity, and the cross section of individual stocks," Journal of Financial Economics, Elsevier, vol. 119(3), pages 489-511.
    55. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
    56. Mishra, Dev R. & O’Brien, Thomas J., 2019. "Fama-French, CAPM, and implied cost of equity," Journal of Economics and Business, Elsevier, vol. 101(C), pages 73-85.
    57. Piao, Xiaorui & Mei, Bin & Xue, Yuan, 2016. "Comparing the financial performance of timber REITs and other REITs," Forest Policy and Economics, Elsevier, vol. 72(C), pages 115-121.
    58. Ilan Cooper & Paulo Maio, 2019. "Asset Growth, Profitability, and Investment Opportunities," Management Science, INFORMS, vol. 65(9), pages 3988-4010, September.
    59. Fabian T. Lutzenberger, 2015. "Multifactor Models and their Consistency with the ICAPM: Evidence from the European Stock Market," European Financial Management, European Financial Management Association, vol. 21(5), pages 1014-1052, November.
    60. Ilan Cooper & Liang Ma & Paulo Maio, 2022. "What Does the Cross‐Section Tell About Itself? Explaining Equity Risk Premia with Stock Return Moments," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(1), pages 73-118, February.
    61. 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.
    62. Leung, Woon Sau & Evans, Kevin P. & Mazouz, Khelifa, 2020. "The R&D anomaly: Risk or mispricing?," Journal of Banking & Finance, Elsevier, vol. 115(C).
    63. Patrizia Perras & Niklas Wagner, 2020. "On the pricing of overnight market risk," Empirical Economics, Springer, vol. 59(3), pages 1307-1327, September.
    64. 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).
    65. Kwon, Ji Ho, 2022. "More predictors of the investment opportunity set in the ICAPM," Finance Research Letters, Elsevier, vol. 47(PA).
    66. Barroso, Pedro & Boons, Martijn & Karehnke, Paul, 2021. "Time-varying state variable risk premia in the ICAPM," Journal of Financial Economics, Elsevier, vol. 139(2), pages 428-451.
    67. González-Urteaga, Ana & Rubio, Gonzalo, 2017. "The joint cross-sectional variation of equity returns and volatilities," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 17-34.
    68. Maio, Paulo & Silva, André C., 2020. "Asset pricing implications of money: New evidence," Journal of Banking & Finance, Elsevier, vol. 120(C).
    69. Andrew Detzel, 2017. "Monetary Policy Surprises, Investment Opportunities, And Asset Prices," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 40(3), pages 315-348, September.
    70. Ekaterini Panopoulou & Sotiria Plastira, 2014. "Fama French factors and US stock return predictability," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 110-128, April.
    71. Kathrin Tauscher & Martin Wallmeier, 2016. "Portfolio Overlapping Bias in Tests of the Fama–French Three†Factor Model," European Financial Management, European Financial Management Association, vol. 22(3), pages 367-393, June.
    72. Boons, M.F., 2014. "Sorting out commodity and macroeconomic risk in expected stock returns," Other publications TiSEM 1ebdac58-bf37-499d-8835-1, Tilburg University, School of Economics and Management.

  5. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    See citations under working paper version above.
  6. Pedro Santa-Clara & Shu Yan, 2010. "Crashes, Volatility, and the Equity Premium: Lessons from S&P 500 Options," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 435-451, May.

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    1. Cheng, Hung-Wen & Lo, Chien-Ling & Tsai, Jeffrey Tzuhao, 2020. "Model specification of conditional jump intensity: Evidence from S&P 500 returns and option prices," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    2. Horvath, Jaroslav, 2019. "Isolating the disaster risk premium with equity options," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 138-148.
    3. Ahsan Habib & Mostafa Monzur Hasan & Haiyan Jiang, 2018. "Stock price crash risk: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 211-251, November.
    4. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2017. "Equity index variance: Evidence from flexible parametric jump–diffusion models," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 85-103.
    5. Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai, 2012. "GARCH Option Valuation: Theory and Evidence," CREATES Research Papers 2012-50, Department of Economics and Business Economics, Aarhus University.
    6. Baruník, Jozef & Bevilacqua, Mattia & Tunaru, Radu, 2022. "Asymmetric network connectedness of fears," LSE Research Online Documents on Economics 108199, London School of Economics and Political Science, LSE Library.
    7. Sangwon Suh & Eungyu Yoo & Sun‐Joong Yoon, 2021. "Stock market tail risk, tail risk premia, and return predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1569-1596, October.
    8. Sang Byung Seo & Jessica A. Wachter, 2019. "Option Prices in a Model with Stochastic Disaster Risk," Management Science, INFORMS, vol. 65(8), pages 3449-3469, August.
    9. Peter Christoffersen & Bruno Feunou & Yoontae Jeon, 2014. "Option Valuation with Observable Volatility and Jump Dynamics," CREATES Research Papers 2015-07, Department of Economics and Business Economics, Aarhus University.
    10. Thorsten Lehnert & Yuehao Lin, 2016. "Skewness Term-Structure Tests," Applied Mathematical Finance, Taylor & Francis Journals, vol. 23(6), pages 484-504, November.
    11. H. Peter Boswijk & Roger J. A. Laeven & Evgenii Vladimirov, 2022. "Estimating Option Pricing Models Using a Characteristic Function Based Linear State Space Representation," Tinbergen Institute Discussion Papers 22-000/III, Tinbergen Institute.
    12. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 119289, London School of Economics and Political Science, LSE Library.
    13. Shuang Li & Yanli Zhou & Yonghong Wu & Xiangyu Ge, 2017. "Equilibrium approach of asset and option pricing under Lévy process and stochastic volatility," Australian Journal of Management, Australian School of Business, vol. 42(2), pages 276-295, May.
    14. Schwarz, Claudia, 2014. "Investor fears and risk premia for rare events," Discussion Papers 03/2014, Deutsche Bundesbank.
    15. Chen, Bei & Gan, Quan & Vasquez, Aurelio, 2023. "Anticipating jumps: Decomposition of straddle price," Journal of Banking & Finance, Elsevier, vol. 149(C).
    16. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
    17. A. S. Hurn & K. A. Lindsay & A. J. McClelland, 2015. "Estimating the Parameters of Stochastic Volatility Models Using Option Price Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 579-594, October.
    18. Christoffersen, Peter & Jacobs, Kris & Ornthanalai, Chayawat, 2012. "Dynamic jump intensities and risk premiums: Evidence from S&P500 returns and options," Journal of Financial Economics, Elsevier, vol. 106(3), pages 447-472.
    19. Jin, Xing & Hong, Yi, 2023. "Jump-diffusion volatility models for variance swaps: An empirical performance analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    20. Yang, Ben-Zhang & Yue, Jia & Wang, Ming-Hui & Huang, Nan-Jing, 2019. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 73-84.
    21. Irfan Safdar & Michael Neel & Babatunde Odusami, 2022. "Accounting information and left-tail risk," Review of Quantitative Finance and Accounting, Springer, vol. 58(4), pages 1709-1740, May.
    22. Carpinteyro, Martha & Venegas Martínez, Francisco & Martínez García, Miguel Ángel, 2019. "Modelado de rendimientos de índices bursátiles mediante movimiento fraccional browniano combinado con procesos de saltos y modulado por cadenas de Markov / Modeling Returns of Stock Indexes through Fr," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 9(2), pages 163-180, julio-dic.
    23. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    24. Gkillas, Konstantinos & Boako, Gideon & Vortelinos, Dimitrios & Vasiliadis, Lavrentios, 2020. "Non-parametric quantile dependencies between volatility discontinuities and political risk," Finance Research Letters, Elsevier, vol. 32(C).
    25. Ballotta, Laura & Rayée, Grégory, 2022. "Smiles & smirks: Volatility and leverage by jumps," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1145-1161.
    26. George M. Constantinides & Jens Carsten Jackwerth & Alexi Savov, 2012. "The Puzzle of Index Option Returns," Working Paper Series of the Department of Economics, University of Konstanz 2012-35, Department of Economics, University of Konstanz.
    27. Xinglin Yang & Peng Wang, 2018. "VIX futures pricing with conditional skewness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1126-1151, September.
    28. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2014. "The Risk Premia Embedded in Index Options," CREATES Research Papers 2014-56, Department of Economics and Business Economics, Aarhus University.
    29. Ornthanalai, Chayawat, 2014. "Lévy jump risk: Evidence from options and returns," Journal of Financial Economics, Elsevier, vol. 112(1), pages 69-90.
    30. Sirio Aramonte, 2022. "Inflation risk and the labor market: beneath the surface of a flat Phillips curve," BIS Working Papers 1054, Bank for International Settlements.
    31. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    32. Jeremy Graveline & Irina Zviadadze & Mikhail Chernov, 2012. "Crash Risk in Currency Returns," 2012 Meeting Papers 753, Society for Economic Dynamics.
    33. Peter Christoffersen & Bruno Feunou & Yoontae Jeon & Chayawat Ornthanalai, 2016. "Time-Varying Crash Risk: The Role of Stock Market Liquidity," Staff Working Papers 16-35, Bank of Canada.
    34. Park, Yang-Ho, 2015. "Volatility-of-volatility and tail risk hedging returns," Journal of Financial Markets, Elsevier, vol. 26(C), pages 38-63.
    35. Jin-Chuan Duan & Weiqi Zhang, 2014. "Forward-Looking Market Risk Premium," Management Science, INFORMS, vol. 60(2), pages 521-538, February.
    36. Mete Kilic & Ivan Shaliastovich, 2019. "Good and Bad Variance Premia and Expected Returns," Management Science, INFORMS, vol. 67(6), pages 2522-2544, June.
    37. Sang Byung Seo & Jessica A. Wachter, 2013. "Option Prices in a Model with Stochastic Disaster Risk," NBER Working Papers 19611, National Bureau of Economic Research, Inc.
    38. Johnson, James A. & Medeiros, Marcelo C. & Paye, Bradley S., 2022. "Jumps in stock prices: New insights from old data," Journal of Financial Markets, Elsevier, vol. 60(C).
    39. Ruan, Xinfeng & Zhu, Wenli & Huang, Jiexiang & Zhang, Jin E., 2016. "Equilibrium asset pricing under the Lévy process with stochastic volatility and moment risk premiums," Economic Modelling, Elsevier, vol. 54(C), pages 326-338.
    40. Li, Bingxin, 2019. "Pricing dynamics of natural gas futures," Energy Economics, Elsevier, vol. 78(C), pages 91-108.
    41. 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.
    42. Aït-Sahalia, Yacine & Xiu, Dacheng, 2016. "Increased correlation among asset classes: Are volatility or jumps to blame, or both?," Journal of Econometrics, Elsevier, vol. 194(2), pages 205-219.
    43. Corbet, Shaen & McMullan, Caroline, 2018. "Stock market reaction to irregular supermarket chain behaviour: An investigation in the retail sectors of Ireland and the United Kingdom," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 20-29.
    44. Benoît Sévi, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Post-Print hal-01500860, HAL.
    45. Câmara, António & Krehbiel, Tim & Li, Weiping, 2011. "Expected returns, risk premia, and volatility surfaces implicit in option market prices," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 215-230, January.
    46. Yuewen Xiao & Xiangkang Yin & Jing Zhao, 2020. "Jumps, News, And Subsequent Return Dynamics: An Intraday Study," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 705-731, August.
    47. Carverhill, Andrew & Luo, Dan, 2023. "A Bayesian analysis of time-varying jump risk in S&P 500 returns and options," Journal of Financial Markets, Elsevier, vol. 64(C).
    48. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    49. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    50. Rama K. Malladi, 2024. "Application of Supervised Machine Learning Techniques to Forecast the COVID-19 U.S. Recession and Stock Market Crash," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1021-1045, March.
    51. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    52. Hasibul Chowdhury & Robert Faff & Khoa Hoang, 2021. "Using abnormal analyst coverage to unlock new evidence on stock price crash risk," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 1557-1588, April.
    53. Ewald, Christian & Zou, Yihan, 2021. "Analytic formulas for futures and options for a linear quadratic jump diffusion model with seasonal stochastic volatility and convenience yield: Do fish jump?," European Journal of Operational Research, Elsevier, vol. 294(2), pages 801-815.
    54. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam, 2019. "An empirical examination of the jump and diffusion aspects of asset pricing: Japanese evidence," Working Papers 2019-02, University of Tasmania, Tasmanian School of Business and Economics.
    55. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," Journal of Financial Markets, Elsevier, vol. 65(C).
    56. Y. Lemp'eri`ere & C. Deremble & T. T. Nguyen & P. Seager & M. Potters & J. P. Bouchaud, 2014. "Risk Premia: Asymmetric Tail Risks and Excess Returns," Papers 1409.7720, arXiv.org, revised Oct 2015.
    57. Hong, Yi & Jin, Xing, 2022. "Pricing of variance swap rates and investment decisions of variance swaps: Evidence from a three-factor model," European Journal of Operational Research, Elsevier, vol. 303(2), pages 975-985.
    58. Barro, Robert J. & Liao, Gordon Y., 2021. "Rare disaster probability and options pricing," Journal of Financial Economics, Elsevier, vol. 139(3), pages 750-769.
    59. Gouriéroux Christian & Monfort Alain & Mouabbi Sarah & Renne Jean-Paul, 2020. "Disastrous Defaults," Working papers 778, Banque de France.
    60. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    61. Aizenman, Joshua & Jinjarak, Yothin & Zheng, Huanhuan, 2016. "Measuring Systemic Risk Contribution of International Mutual Funds," ADBI Working Papers 594, Asian Development Bank Institute.
    62. Michal Czerwonko & Stylianos Perrakis, 2016. "Portfolio Selection with Transaction Costs and Jump-Diffusion Asset Dynamics I: A Numerical Solution," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 1-23, December.
    63. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2020. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 118850, London School of Economics and Political Science, LSE Library.
    64. Byun, Suk Joon & Jeon, Byoung Hyun & Min, Byungsun & Yoon, Sun-Joong, 2015. "The role of the variance premium in Jump-GARCH option pricing models," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 38-56.
    65. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch & Seong-Min Yoon, 2020. "OPEC News and Jumps in the Oil Market," Working Papers 202053, University of Pretoria, Department of Economics.
    66. Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2020. "Oil shocks and volatility jumps," Review of Quantitative Finance and Accounting, Springer, vol. 54(1), pages 247-272, January.
    67. Ben-zhang Yang & Jia Yue & Ming-hui Wang & Nan-jing Huang, 2018. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Papers 1805.06226, arXiv.org, revised May 2018.
    68. Jozef Barunik & Mattia Bevilacqua & Robert Faff, 2021. "Dynamic industry uncertainty networks and the business cycle," Papers 2101.06957, arXiv.org, revised Mar 2021.
    69. Liu, Xiaoquan & Cao, Yi & Ma, Chenghu & Shen, Liya, 2019. "Wavelet-based option pricing: An empirical study," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1132-1142.
    70. Wu, Liuren, 2018. "Estimating risk-return relations with analysts price targets," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 183-197.
    71. Chung, Kee H. & Wang, Junbo & Wu, Chunchi, 2019. "Volatility and the cross-section of corporate bond returns," Journal of Financial Economics, Elsevier, vol. 133(2), pages 397-417.
    72. Lee, Kiryoung & Jeon, Yoontae & Nam, Eun-Young, 2021. "Chinese Economic Policy Uncertainty and the Cross-Section of U.S. Asset Returns," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1063-1077.
    73. Li, Gang & Zhang, Chu, 2016. "On the relationship between conditional jump intensity and diffusive volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 196-213.
    74. Branger, Nicole & Rodrigues, Paulo & Schlag, Christian, 2018. "Level and slope of volatility smiles in long-run risk models," Journal of Economic Dynamics and Control, Elsevier, vol. 86(C), pages 95-122.
    75. Peter Reinhard Hansen & Zhuo Huang & Chen Tong & Tianyi Wang, 2021. "Realized GARCH, CBOE VIX, and the Volatility Risk Premium," Papers 2112.05302, arXiv.org.
    76. Carpinteyro, Martha & Venegas-Martínez, Francisco & Martínez-García, Miguel Ángel, 2018. "Modeling Returns of Stock Indexes through Fractional Brownian Motion Combined with Jump Processes and Modulated by Markov Chains," MPRA Paper 90549, University Library of Munich, Germany.
    77. Bingxin Li, 2020. "Option-implied filtering: evidence from the GARCH option pricing model," Review of Quantitative Finance and Accounting, Springer, vol. 54(3), pages 1037-1057, April.
    78. Dinesh Gajurel & Mardi Dungey & Wenying Yao & Nagaratnam Jeyasreedharan, 2020. "Jump Risk in the US Financial Sector," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 331-349, September.
    79. William N. Goetzmann & Dasol Kim & Robert J. Shiller, 2016. "Crash Beliefs From Investor Surveys," NBER Working Papers 22143, National Bureau of Economic Research, Inc.
    80. Bai, Jennie & Goldstein, Robert S. & Yang, Fan, 2020. "Is the credit spread puzzle a myth?," Journal of Financial Economics, Elsevier, vol. 137(2), pages 297-319.
    81. 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.
    82. Branger, Nicole & Rodrigues, Paulo & Schlag, Christian, 2017. "Level and slope of volatility smiles in Long-Run Risk Models," SAFE Working Paper Series 186, Leibniz Institute for Financial Research SAFE.
    83. Chen, Xi & Wang, Junbo & Wu, Chunchi, 2022. "Jump and volatility risk in the cross-section of corporate bond returns," Journal of Financial Markets, Elsevier, vol. 60(C).
    84. Max Gillman & Michal Kejak & Michal Pakos, 2014. "Learning about Rare Disasters: Implications for Consumptions and Asset Prices," CEU Working Papers 2014_2, Department of Economics, Central European University.
    85. 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.
    86. Reyes-García, Nallely Jacqueline & Venegas-Martínez, Francisco & Cruz-Aké, Salvador, 2018. "Un análisis comparativo entre GARCH-M, EGARCH y PJ-RS-EV para modelar la volatilidad de Índice de precios y cotizaciones de la Bolsa Mexicana de Valores [A Comparative Analysis among GARCH-M, EGARC," MPRA Paper 84304, University Library of Munich, Germany.
    87. Robert J. Barro & Gordon Y. Liao, 2019. "Tractable Rare Disaster Probability and Options-Pricing," Finance and Economics Discussion Series 2019-073, Board of Governors of the Federal Reserve System (U.S.).
    88. Lerby Ergun, 2019. "Extreme Downside Risk in Asset Returns," Staff Working Papers 19-46, Bank of Canada.
    89. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2018. "The Pricing of Tail Risk and the Equity Premium: Evidence from International Option Markets," CREATES Research Papers 2018-02, Department of Economics and Business Economics, Aarhus University.
    90. Chen, Chin-Ho, 2019. "Downside jump risk and the levels of futures-cash basis," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    91. Yoon, Sun-Joong, 2017. "Time-varying risk aversion and return predictability," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 327-339.
    92. Jin E. Zhang & Eric C. Chang & Huimin Zhao, 2020. "Market Excess Returns, Variance and the Third Cumulant," International Review of Finance, International Review of Finance Ltd., vol. 20(3), pages 605-637, September.
    93. Ewald, Christian & Zou, Yihan, 2021. "Stochastic volatility: A tale of co-jumps, non-normality, GMM and high frequency data," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 37-52.
    94. 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.
    95. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Uribe, Jorge M., 2022. "Spillovers beyond the variance: Exploring the higher order risk linkages between commodity markets and global financial markets," Journal of Commodity Markets, Elsevier, vol. 28(C).
    96. Hsuan‐Ling Chang & Yen‐Cheng Chang & Hung‐Wen Cheng & Po‐Hsiang Peng & Kevin Tseng, 2019. "Jump variance risk: Evidence from option valuation and stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 890-915, July.
    97. 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.
    98. Kent Wang & Yuqiang Guo, 2014. "Predictability of time-varying jump premiums: Evidence based on calibration," Australian Journal of Management, Australian School of Business, vol. 39(3), pages 369-394, August.
    99. George Chalamandaris & Leonidas S. Rompolis, 2021. "Recovering the market risk premium from higher‐order moment risks," European Financial Management, European Financial Management Association, vol. 27(1), pages 147-186, January.
    100. Peter Christoffersen & Mathieu Fournier & Kris Jacobs, 2018. "The Factor Structure in Equity Options," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 595-637.
    101. Jianjian Jin, 2015. "Jump-Diffusion Long-Run Risks Models, Variance Risk Premium, and Volatility Dynamics," Review of Finance, European Finance Association, vol. 19(3), pages 1223-1279.
    102. Saranya Kshatriya & Krishna Prasanna, 2020. "Unveiling Contemporaneous Relations Between Jump Risk and Cross Section of Stock Returns," International Review of Finance, International Review of Finance Ltd., vol. 20(3), pages 581-604, September.
    103. Bates, David S., 2012. "U.S. stock market crash risk, 1926–2010," Journal of Financial Economics, Elsevier, vol. 105(2), pages 229-259.
    104. Bas Peeters, 2012. "Risk premiums in a simple market model for implied volatility," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 739-748, January.
    105. Oliver X. Li & Weiping Li, 2015. "Hedging jump risk, expected returns and risk premia in jump-diffusion economies," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 873-888, May.
    106. Yan, Shu, 2011. "Jump risk, stock returns, and slope of implied volatility smile," Journal of Financial Economics, Elsevier, vol. 99(1), pages 216-233, January.
    107. Huang, Chun-Sung & O'Hara, John G. & Mataramvura, Sure, 2022. "Highly efficient Shannon wavelet-based pricing of power options under the double exponential jump framework with stochastic jump intensity and volatility," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    108. Chernov, Mikhail & Graveline, Jeremy & Zviadadze, Irina, 2012. "Sources of Risk in Currency Returns," CEPR Discussion Papers 8745, C.E.P.R. Discussion Papers.
    109. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2018. "Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 1-29.
    110. Katherine B. Ensor & Yu Han & Barbara Ostdiek & Stuart M. Turnbull, 2020. "Dynamic jump intensities and news arrival in oil futures markets," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 292-325, July.
    111. Lu, Zhongjin & Murray, Scott, 2019. "Bear beta," Journal of Financial Economics, Elsevier, vol. 131(3), pages 736-760.
    112. Bruno Feunou & Ricardo Lopez Aliouchkin & Roméo Tedongap & Lai Xu, 2020. "The Term Structures of Loss and Gain Uncertainty," Staff Working Papers 20-19, Bank of Canada.
    113. Yang Lu & Michael Siemer, 2013. "Learning, Rare Disasters, and Asset Prices," Finance and Economics Discussion Series 2013-85, Board of Governors of the Federal Reserve System (U.S.).
    114. Slim, Skander, 2016. "On the source of stochastic volatility: Evidence from CAC40 index options during the subprime crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 63-76.

  7. Michael W. Brandt & Pedro Santa-Clara & Rossen Valkanov, 2009. "Parametric Portfolio Policies: Exploiting Characteristics in the Cross-Section of Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3411-3447, September.
    See citations under working paper version above.
  8. Santa-Clara, Pedro & Saretto, Alessio, 2009. "Option strategies: Good deals and margin calls," Journal of Financial Markets, Elsevier, vol. 12(3), pages 391-417, August.
    See citations under working paper version above.
  9. John H. Cochrane & Francis A. Longstaff & Pedro Santa-Clara, 2008. "Two Trees," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 347-385, January.
    See citations under working paper version above.
  10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    See citations under working paper version above.
  11. Brandt, Michael W. & Cochrane, John H. & Santa-Clara, Pedro, 2006. "International risk sharing is better than you think, or exchange rates are too smooth," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 671-698, May.

    Cited by:

    1. Martin Bodenstein, 2006. "International Asset Markets and Real Exchange Rate Volatility," International Finance Discussion Papers 884, Board of Governors of the Federal Reserve System (U.S.).
    2. De Santis, Roberto A. & Sarno, Lucio, 2008. "Assessing the benefits of international portfolio diversification in bonds and stocks," Working Paper Series 883, European Central Bank.
    3. Hakon Tretvoll, 2018. "Real Exchange Variability in a Two-Country Business Cycle Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 27, pages 123-145, January.
    4. Karen K. Lewis, 2011. "Global Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 3(1), pages 435-466, December.
    5. Costa, Carlos Eugênio da & Issler, João Victor & Matos, Paulo Rogério Faustino, 2009. "The forward- and the equity-premium puzzles: two symptoms of the same illness?," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 697, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    6. Adrien Verdelhan, 2012. "The Share of Systematic Variation in Bilateral Exchange Rates," 2012 Meeting Papers 763, Society for Economic Dynamics.
    7. Mo, Henry & Wu, Liuren, 2007. "International capital asset pricing: Evidence from options," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 465-498, September.
    8. Mueller, Philippe & Stathopoulos, Andreas & Vedolin, Andrea, 2014. "International correlation risk," LSE Research Online Documents on Economics 60955, London School of Economics and Political Science, LSE Library.
    9. Pavlova, Anna & Rigobon, Roberto, 2004. "Asset Prices and Exchange Rates," Working papers 4322-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    10. Hoffmann, Mathias, 2008. "International financial markets' influence on the welfare performance of alternative exchange rate regimes," Discussion Paper Series 1: Economic Studies 2008,27, Deutsche Bundesbank.
    11. Martin Melecky, 2008. "A Structural Investigation of Third‐Currency Shocks to Bilateral Exchange Rates," International Finance, Wiley Blackwell, vol. 11(1), pages 19-48, May.
    12. Simona E. Cociuba & Ananth Ramanarayanan, 2011. "International Risk Sharing with Endogenously Segmented Asset Markets," 2011 Meeting Papers 853, Society for Economic Dynamics.
    13. Jotikasthira, Chotibhak & Le, Anh & Lundblad, Christian, 2015. "Why do term structures in different currencies co-move?," Journal of Financial Economics, Elsevier, vol. 115(1), pages 58-83.
    14. Charles Engel, 2013. "Exchange Rates and Interest Parity," NBER Working Papers 19336, National Bureau of Economic Research, Inc.
    15. Charles Engel & John H. Rogers, 2008. "Expected consumption growth from cross-country surveys: implications for assessing international capital markets," International Finance Discussion Papers 949, Board of Governors of the Federal Reserve System (U.S.).
    16. Fernandes, Marcelo & Vieira Filho, Jose Gil, 2020. "The efficiency of risk sharing between UK and US: Robust estimation and calibration under market incompleteness," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 39(2), March.
    17. Giuseppe Cavaliere & Luca Fanelli & Attilio Gardini, 2008. "International dynamic risk sharing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 1-16.
    18. 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.
    19. Federico Gavazzoni & Ana Maria Santacreu, 2015. "International R&D Spillovers and Asset Prices," Working Papers 2015-41, Federal Reserve Bank of St. Louis.
    20. De Paoli, Bianca & Scott, Alasdair & Weeken, Olaf, 2010. "Asset pricing implications of a New Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2056-2073, October.
    21. Andreas Stathopoulos, 2012. "Portfolio Home Bias and External Habit Formation," 2012 Meeting Papers 502, Society for Economic Dynamics.
    22. Alessandro Ferrari & Anna Rogantini Picco, 2016. "International Risk Sharing in the EMU," Working Papers 17, European Stability Mechanism.
    23. Charles Engel, 2015. "Exchange Rates, Interest Rates, and the Risk Premium," NBER Working Papers 21042, National Bureau of Economic Research, Inc.
    24. Ravi Bansal, 2007. "Long-run risks and financial markets," Review, Federal Reserve Bank of St. Louis, vol. 89(Jul), pages 283-300.
    25. Giancarlo Corsetti & Luca Dedola & Francesca Viani, 2012. "Traded and nontraded goods prices, and international risk sharing: an empirical investigation," Working Papers 1242, Banco de España.
    26. Engel, Charles, 2011. "The Real Exchange Rate, Real Interest Rates, and the Risk Premium," Economics Series 265, Institute for Advanced Studies.
    27. Chernov, Mikhail & Creal, Drew, 2022. "International yield curves and currency puzzles," CEPR Discussion Papers 13252, C.E.P.R. Discussion Papers.
    28. Narayana R. Kocherlakota & Luigi Pistaferri, 2007. "Household Heterogeneity and Real Exchange Rates," Economic Journal, Royal Economic Society, vol. 117(519), pages 1-25, March.
    29. Jiang, Zhengyang & Krishnamurthy, Arvind & Lustig, Hanno, 2018. "Foreign Safe Asset Demand and the Dollar Exchange Rate," Research Papers 3621, Stanford University, Graduate School of Business.
    30. Emmanuel Farhi & Xavier Gabaix, "undated". "Rare Disasters and Exchange Rates," Working Paper 71001, Harvard University OpenScholar.
    31. Zhang, Shaojun, 2016. "Limited Risk Sharing and International Equity Returns," Working Paper Series 2016-25, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    32. Hanno Lustig & Andreas Stathopoulos & Adrien Verdelhan, 2013. "The Term Structure of Currency Carry Trade Risk Premia," NBER Working Papers 19623, National Bureau of Economic Research, Inc.
    33. Hanno Lustig & Adrien Verdelhan, 2019. "Does Incomplete Spanning in International Financial Markets Help to Explain Exchange Rates?," American Economic Review, American Economic Association, vol. 109(6), pages 2208-2244, June.
    34. Huang, Lin & Wu, Jia & Zhang, Rui, 2014. "Exchange risk and asset returns: A theoretical and empirical study of an open economy asset pricing model," Emerging Markets Review, Elsevier, vol. 21(C), pages 96-116.
    35. Jonathan Heathcote & Fabrizio Perri, 2013. "Assessing international efficiency," Staff Report 480, Federal Reserve Bank of Minneapolis.
    36. David K. Backus & Federico Gavazzoni & Christopher Telmer & Stanley E. Zin, 2010. "Monetary Policy and the Uncovered Interest Parity Puzzle," NBER Working Papers 16218, National Bureau of Economic Research, Inc.
    37. Lorenzo Cappiello & Nikolaos Panigirtzoglou, 2008. "Estimates of foreign exchange risk premia: a pricing kernel approach," Empirical Economics, Springer, vol. 35(3), pages 475-495, November.
    38. Pietro Cova & Mr. Alessandro Rebucci & Mr. Akito Matsumoto & Massimiliano Pisani, 2008. "New Shocks, Exchange Rates and Equity Prices," IMF Working Papers 2008/284, International Monetary Fund.
    39. Bakshi, Gurdip & Carr, Peter & Wu, Liuren, 2008. "Stochastic risk premiums, stochastic skewness in currency options, and stochastic discount factors in international economies," Journal of Financial Economics, Elsevier, vol. 87(1), pages 132-156, January.
    40. Epstein, Brendan & Mukherjee, Rahul & Ramnath, Shanthi, 2016. "Taxes and international risk sharing," Journal of International Economics, Elsevier, vol. 102(C), pages 310-326.
    41. Basu, Parantap & Wada, Kenji, 2006. "Is low international risk sharing consistent with a high equity premium? A reconciliation of two puzzles," Economics Letters, Elsevier, vol. 93(3), pages 436-442, December.
    42. Sercu, Piet & Vandebroek, Martina & Wu, Xueping, 2008. "Is the forward bias economically small? Evidence from European rates," Journal of International Money and Finance, Elsevier, vol. 27(8), pages 1284-1302, December.
    43. Fabrizio Perri & Jonathan Heathcote, 2015. "On the desirability of capital controls," 2015 Meeting Papers 1349, Society for Economic Dynamics.
    44. Michael B. Devereux & Gregor W. Smith & James Yetman, 2009. "Consumption and Real Exchange Rates in Professional Forecasts," NBER Working Papers 14795, National Bureau of Economic Research, Inc.
    45. Gerdie Everaert & Lorenzo Pozzi, 2022. "Encompassing measures of international consumption risk sharing and their link with trade and financial globalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 433-449, March.
    46. Hassan, Ramin & Loualiche, Erik & Pecora, Alexandre R. & Ward, Colin, 2023. "International trade and the risk in bilateral exchange rates," Journal of Financial Economics, Elsevier, vol. 150(2).
    47. da Costa, Carlos E. & Issler, João V. & Matos, Paulo F., 2015. "A Note On The Forward And The Equity Premium Puzzles: Two Symptoms Of The Same Illness?," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 446-464, March.
    48. Gourio, François & Siemer, Michael & Verdelhan, Adrien, 2013. "International risk cycles," Journal of International Economics, Elsevier, vol. 89(2), pages 471-484.
    49. Oleg Itskhoki, 2021. "The Story of the Real Exchange Rate," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 423-455, August.
    50. Balvers, Ronald J. & Klein, Alina F., 2014. "Currency risk premia and uncovered interest parity in the International CAPM," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 214-230.
    51. Hanno Lustig & Andreas Stathopoulos & Adrien Verdelhan, 2019. "The Term Structure of Currency Carry Trade Risk Premia," American Economic Review, American Economic Association, vol. 109(12), pages 4142-4177, December.
    52. M. Hadzi-Vaskov & C.J.M. Kool, 2007. "Stochastic Discount Factor Approach to International Risk-Sharing: Evidence from Fixed Exchange Rate Episodes," Working Papers 07-33, Utrecht School of Economics.
    53. Jairo A. Rendon, 2019. "Global And Regional Risks In Currency Returns," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(08), pages 1-25, December.
    54. Fousseni Chabi-Yo & Riccardo Colacito, 2019. "The Term Structures of Coentropy in International Financial Markets," Management Science, INFORMS, vol. 65(8), pages 3541-3558, August.
    55. Adrien Verdelhan, 2006. "A Habit-Based Explanation of the Exchange Rate Risk Premium," Computing in Economics and Finance 2006 217, Society for Computational Economics.
    56. Jianfeng Yu, 2011. "A sentiment-based explanation of the forward premium puzzle," Globalization Institute Working Papers 90, Federal Reserve Bank of Dallas.
    57. Chan R. Mang, 2014. "Uncertain Risk and Return in Bond Markets, I," 2014 Papers pma1706, Job Market Papers.
    58. Fang, Xiang & Liu, Yang, 2021. "Volatility, intermediaries, and exchange rates," Journal of Financial Economics, Elsevier, vol. 141(1), pages 217-233.
    59. Kraft, Holger & Meyer-Wehmann, André & Seifried, Frank Thomas, 2022. "Endogenous habits and equilibrium asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 279-300.
    60. Thomas Nitschka, 2009. "Momentum in stock market returns, risk premia on foreign currencies and international financial integration," IEW - Working Papers 405, Institute for Empirical Research in Economics - University of Zurich.
    61. Paulo Rogério Faustino Matos, 2019. "The role of household debt and delinquency decisions in consumption-based asset pricing," Annals of Finance, Springer, vol. 15(2), pages 179-203, June.
    62. Carrasco-Gutierrez, Carlos Enrique & Piazza, Wagner, 2011. "Evaluating Asset Pricing Models in a Simulated Multifactor Approach," MPRA Paper 66063, University Library of Munich, Germany, revised 2012.
    63. Metodij Hadzi-Vaskov & Clemens J.M. Kool, 2007. "Stochastic Discount Factor Approach to International Risk-Sharing: A Trilateral Framework," EcoMod2007 23900031, EcoMod.
    64. Hanno Lustig & Adrien Verdelhan, 2016. "Does Incomplete Spanning in International Financial Markets Help to Explain Exchange Rates?," NBER Working Papers 22023, National Bureau of Economic Research, Inc.
    65. YiLi Chien & Hanno Lustig & Kanda Naknoi, 2015. "Why Are Exchange Rates So Smooth? A Household Finance Explanation," Working Papers 2015-39, Federal Reserve Bank of St. Louis.
    66. Fernando Alvarez & Andrew Atkeson & Patrick J. Kehoe, 2005. "Time-varying risk, interest rates and exchange rates in general equilibrium," Working Papers 627, Federal Reserve Bank of Minneapolis.
    67. A. Craig Burnside & Jeremy J. Graveline, 2012. "On the Asset Market View of Exchange Rates," NBER Working Papers 18646, National Bureau of Economic Research, Inc.
    68. Fernando Alvarez & Andrew Atkeson & Patrick J. Kehoe, 2007. "If exchange rates are random walks, then almost everything we say about monetary policy is wrong," Staff Report 388, Federal Reserve Bank of Minneapolis.
    69. Carlos Enrique Carrasco Gutierrez & Wagner Piazza Gaglianone, 2008. "Evaluating Asset Pricing Models in a Fama-French Framework," Working Papers Series 175, Central Bank of Brazil, Research Department.
    70. Lee, Eunhee, 2019. "Asset prices with stochastic volatilities and a UIP puzzle," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 41-61.
    71. Hornstein, Abigail S. & Naknoi, Kanda, 2023. "FDI commitments increase when uncertainty is resolved: Evidence from Asia," Journal of Asian Economics, Elsevier, vol. 87(C).
    72. Vedolin, Andrea & Korsaye, Sofonias Alemu & Trojani, Fabio, 2020. "The Global Factor Structure of Exchange Rates," CEPR Discussion Papers 15337, C.E.P.R. Discussion Papers.
    73. Kanda Naknoi & Hanno Lustig & YiLi Chien, 2017. "Why Are Exchange Rates So Smooth? A Heterogeneous Portfolio Explanation," 2017 Meeting Papers 214, Society for Economic Dynamics.
    74. Anella Munro, 2016. "Bond premia, monetary policy and exchange rate dynamics," Reserve Bank of New Zealand Discussion Paper Series DP2016/11, Reserve Bank of New Zealand.
    75. Ferreira, Alex & Matos, Paulo, 2020. "Precautionary risks for an open economy," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 154-167.
    76. Croce, Mariano & Gavazzoni, Federico & Colacito, Ric & Ready, Robert, 2018. "Currency Risk Factors in a Recursive Multicountry Economy," CEPR Discussion Papers 12610, C.E.P.R. Discussion Papers.
    77. Basu, Parantap & Semenov, Andrei & Wada, Kenji, 2009. "Uninsurable Risk and Financial Market Puzzles," MPRA Paper 23351, University Library of Munich, Germany.
    78. Yuming Li & Maosen Zhong, 2009. "International asset returns and exchange rates," The European Journal of Finance, Taylor & Francis Journals, vol. 15(3), pages 263-285.
    79. Chu, Shiou-Yen, 2015. "Funding liquidity constraints and the forward premium anomaly in a DSGE model," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 76-89.
    80. Ibrahim Ayoade Adekunle & Sheriffdeen Adewale Tella & Oluwaseyi Adedayo Adelowokan, 2021. "Macroeconomic policy volatility and household consumption in Africa," SN Business & Economics, Springer, vol. 1(3), pages 1-22, March.
    81. Matteo Maggiori, 2013. "The U.S. Dollar Safety Premium," 2013 Meeting Papers 75, Society for Economic Dynamics.
    82. Moore, Michael J. & Roche, Maurice J., 2010. "Solving exchange rate puzzles with neither sticky prices nor trade costs," Journal of International Money and Finance, Elsevier, vol. 29(6), pages 1151-1170, October.
    83. Gurdip Bakshi & Xiaohui Gao & George Panayotov, 2021. "A Theory of Dissimilarity Between Stochastic Discount Factors," Management Science, INFORMS, vol. 67(7), pages 4602-4622, July.
    84. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2018. "Common information in carry trade risk factors," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 37-47.
    85. Clancy, Daragh & Ricci, Lorenzo, 2022. "Economic sentiments and international risk sharing," International Economics, Elsevier, vol. 169(C), pages 208-229.
    86. Gianluca Benigno & Pierpaolo Benigno & Salvatore Nisticò, 2011. "Risk, Monetary Policy and the Exchange Rate," NBER Chapters, in: NBER Macroeconomics Annual 2011, Volume 26, pages 247-309, National Bureau of Economic Research, Inc.
    87. Wenxin Du & Carolin E. Pflueger & Jesse Schreger, 2016. "Sovereign Debt Portfolios, Bond Risks, and the Credibility of Monetary Policy," NBER Working Papers 22592, National Bureau of Economic Research, Inc.
    88. Andreas Stathopoulos & Adrien Verdelhan & Hanno Lustig, 2017. "Nominal Exchange Rate Stationarity and Long-Term Bond Returns," 2017 Meeting Papers 1633, Society for Economic Dynamics.
    89. Emi Nakamura & Dmitriy Sergeyev & Jón Steinsson, 2012. "Growth-Rate and Uncertainty Shocks in Consumption: Cross-Country Evidence," NBER Working Papers 18128, National Bureau of Economic Research, Inc.
    90. Mariano M. Croce & Riccardo Colacito, 2010. "International Asset Pricing with Risk-Sensitive Rare Events," 2010 Meeting Papers 176, Society for Economic Dynamics.
    91. Evžen Koèenda & Tigran Poghosyan, 2010. "Exchange Rate Risk in Central European Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(1), pages 22-39, February.
    92. Mr. Phurichai Rungcharoenkitkul, 2011. "Risk Sharing and Financial Contagion in Asia: An Asset Price Perspective," IMF Working Papers 2011/242, International Monetary Fund.
    93. Mueller, Philippe & Stathopoulos, Andreas & Vedolin, Andrea, 2013. "International correlation risk," LSE Research Online Documents on Economics 43087, London School of Economics and Political Science, LSE Library.
    94. Gurdip Bakshi & Mario Cerrato & John Crosby, 2016. "Studying the Implications of Consumption and Asset Return Data for Stochastic Discount Factors in Incomplete International Economies," Working Papers 2017_01, Business School - Economics, University of Glasgow.
    95. Mr. Marco Terrones & Mr. Ayhan Kose & Mr. Eswar S Prasad, 2007. "How Does Financial Globalization Affect Risk Sharing? Patterns and Channels," IMF Working Papers 2007/238, International Monetary Fund.
    96. Maurer, Thomas & Tran, Ngoc-Khanh, 2021. "Entangled risks in incomplete FX markets," Journal of Financial Economics, Elsevier, vol. 142(1), pages 146-165.
    97. Curatola, Giuliano & Dergunov, Ilya, 2023. "International capital markets with interdependent preferences: Theory and empirical evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 403-421.
    98. Wang, Xi & Yang, Jiao-Hui & Wang, Kai-Li & Fawson, Christopher, 2017. "Dynamic information spillovers in intraregionally-focused spot and forward currency markets," Journal of International Money and Finance, Elsevier, vol. 71(C), pages 78-110.
    99. Yin, Weiwei & Li, Junye, 2014. "Macroeconomic fundamentals and the exchange rate dynamics: A no-arbitrage macro-finance approach," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 46-64.
    100. Hanno Lustig & Nikolai Roussanov & Adrien Verdelhan, 2010. "Countercyclical Currency Risk Premia," NBER Working Papers 16427, National Bureau of Economic Research, Inc.
    101. Yu, Changhua, 2015. "Evaluating international financial integration in a center-periphery economy," Journal of International Economics, Elsevier, vol. 95(1), pages 129-144.
    102. Yu, Jianfeng, 2013. "A sentiment-based explanation of the forward premium puzzle," Journal of Monetary Economics, Elsevier, vol. 60(4), pages 474-491.
    103. Bakshi, Gurdip & Madan, Dilip & Panayotov, George, 2010. "Returns of claims on the upside and the viability of U-shaped pricing kernels," Journal of Financial Economics, Elsevier, vol. 97(1), pages 130-154, July.
    104. Ana Maria Santacreu & Federico Gavazzoni, 2014. "International Comovement through Endogenous Long Run Risk," 2014 Meeting Papers 993, Society for Economic Dynamics.
    105. Fousseni Chabi-Yo & Jun Yang, 2007. "A No-Arbitrage Analysis of Macroeconomic Determinants of Term Structures and the Exchange Rate," Staff Working Papers 07-21, Bank of Canada.
    106. Borja Larrain, 2005. "The stock market and cross country differences in relative prices," Working Papers 05-6, Federal Reserve Bank of Boston.
    107. Thomas A. Maurer & Thuy-Duong Tô & Ngoc-Khanh Tran, 2019. "Pricing Risks Across Currency Denominations," Management Science, INFORMS, vol. 65(11), pages 5308-5336, November.
    108. Daragh Clancy & Lorenzo Ricci, 2019. "Loss aversion, economic sentiments and international consumption smoothing," Working Papers 35, European Stability Mechanism.
    109. Korsaye, Sofonias Alemu & Trojani, Fabio & Vedolin, Andrea, 2023. "The global factor structure of exchange rates," Journal of Financial Economics, Elsevier, vol. 148(1), pages 21-46.
    110. 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.
    111. Ian Martin, 2011. "The Forward Premium Puzzle in a Two-Country World," NBER Working Papers 17564, National Bureau of Economic Research, Inc.
    112. Arash Aloosh & Geert Bekaert, 2019. "Currency Factors," NBER Working Papers 25449, National Bureau of Economic Research, Inc.
    113. Chang, Sanders S., 2013. "Can cross-country portfolio rebalancing give rise to forward bias in FX markets?," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1079-1096.
    114. Karen K. Lewis & Edith X. Liu, 2012. "International Consumption Risk Is Shared After All: An Asset Return View," NBER Working Papers 17872, National Bureau of Economic Research, Inc.
    115. Lewis, Karen K. & Liu, Edith X., 2015. "Evaluating international consumption risk sharing gains: An asset return view," Journal of Monetary Economics, Elsevier, vol. 71(C), pages 84-98.
    116. George M. Korniotis & Alok Kumar, 2008. "Do behavioral biases adversely affect the macro-economy?," Finance and Economics Discussion Series 2008-49, Board of Governors of the Federal Reserve System (U.S.).
    117. Vasilyev, Dmitry (Васильев, Дмитрий) & Busygin, Vladimir (Бусыгин, Владимир) & Busygin, Sergei (Бусыгин, Сергей), 2016. "Testing and Interpreting Uncovered Interest Parity in Russia [Проверка И Интерпретация Выполнения Процентного Паритета В России]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 4, pages 35-55, August.
    118. M. Hadzi-Vaskov & C.J.M. Kool, 2007. "Stochastic Discount Factor Approach to International Risk-Sharing:A Robustness Check of the Bilateral Setting," Working Papers 07-34, Utrecht School of Economics.
    119. Cevdet Aydemir, A., 2008. "Risk sharing and counter-cyclical variation in market correlations," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3084-3112, October.
    120. Mathias Hoffmann & Thomas Nitschka, 2007. "The Consumption - Real Exchange Rate Anomaly: an Asset Pricing Perspective," IEW - Working Papers 331, Institute for Empirical Research in Economics - University of Zurich.
    121. Branger, Nicole & Herold, Michael & Muck, Matthias, 2021. "International stochastic discount factors and covariance risk," Journal of Banking & Finance, Elsevier, vol. 123(C).
    122. Mirela Sandulescu & Fabio Trojani & Andrea Vedolin, 2021. "Model‐Free International Stochastic Discount Factors," Journal of Finance, American Finance Association, vol. 76(2), pages 935-976, April.
    123. Asdrubali, Pierfederico & Kim, Soyoung & Pericoli, Filippo & Poncela, Pilar, 2018. "New Risk Sharing Channels in OECD Countries: a Heterogeneous Panel VAR," Working Papers 2018-13, Joint Research Centre, European Commission.
    124. Orlov, Vitaly, 2016. "Currency momentum, carry trade, and market illiquidity," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 1-11.
    125. Chang, Yanqin, 2007. "high level of international risk sharing when the productivity growth contains long run risk," MPRA Paper 4476, University Library of Munich, Germany.
    126. Gurdip Bakashi & Mario Cerrato & John Crosby, 2015. "Risk Sharing in International Economies and Market Incompleteness," Working Papers 2015_23, Business School - Economics, University of Glasgow.
    127. Kim, H. Youn, 2014. "International financial integration and risk sharing among countries: A production-based approach," Journal of the Japanese and International Economies, Elsevier, vol. 31(C), pages 16-35.
    128. EnDer Su, 2018. "Measuring contagion risk in high volatility state among Taiwanese major banks," Risk Management, Palgrave Macmillan, vol. 20(3), pages 185-241, August.
    129. Du, Du, 2013. "General equilibrium pricing of currency and currency options," Journal of Financial Economics, Elsevier, vol. 110(3), pages 730-751.
    130. Xinglin Yang, 2023. "Unspanned macro risks in VIX futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1305-1328, September.
    131. M. Hadzi-Vaskov, 2007. "Does the Nominal Exchange Rate Explain the Backus-Smith Puzzle? Evidence from the Eurozone," Working Papers 07-32, Utrecht School of Economics.

  12. Michael W. Brandt & Pedro Santa‐Clara, 2006. "Dynamic Portfolio Selection by Augmenting the Asset Space," Journal of Finance, American Finance Association, vol. 61(5), pages 2187-2217, October.
    See citations under working paper version above.
  13. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan R. Stroud, 2005. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 831-873.
    See citations under working paper version above.
  14. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    See citations under working paper version above.
  15. Olivier Ledoit & Pedro Santa-Clara & Michael Wolf, 2003. "Flexible Multivariate GARCH Modeling with an Application to International Stock Markets," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 735-747, August.
    See citations under working paper version above.
  16. Brandt, Michael W. & Santa-Clara, Pedro, 2002. "Simulated likelihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets," Journal of Financial Economics, Elsevier, vol. 63(2), pages 161-210, February.
    See citations under working paper version above.
  17. Santa-Clara, Pedro & Sornette, Didier, 2001. "The Dynamics of the Forward Interest Rate Curve with Stochastic String Shocks," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 149-185.
    See citations under working paper version above.
  18. Longstaff, Francis A. & Santa-Clara, Pedro & Schwartz, Eduardo S., 2001. "Throwing away a billion dollars: the cost of suboptimal exercise strategies in the swaptions market," Journal of Financial Economics, Elsevier, vol. 62(1), pages 39-66, October.

    Cited by:

    1. Longstaff, Francis A., 2002. "Optimal Recursive Refinancing and the Valuation of Mortgage-Backed Securities," University of California at Los Angeles, Anderson Graduate School of Management qt19k7479t, Anderson Graduate School of Management, UCLA.
    2. Sami Attaoui, 2011. "Hedging performance of the Libor market model: the cap market case," Post-Print hal-00653437, HAL.
    3. Raoul Pietersz & Antoon Pelsser, 2005. "A Comparison of Single Factor Markov-functional and Multi Factor Market Models," Finance 0502008, University Library of Munich, Germany.
    4. Laruent Barras, 2005. "International Conditional Asset Allocation under Real Time Uncertrainty," FAME Research Paper Series rp153, International Center for Financial Asset Management and Engineering.
    5. Kerkhof, F.L.J. & Pelsser, A., 2002. "Observational Equivalence of Discrete String Models and Market Models," Other publications TiSEM adbe78f4-8729-4f92-ba2b-6, Tilburg University, School of Economics and Management.
    6. Pierre Collin‐Dufresne & Robert S. Goldstein, 2002. "Do Bonds Span the Fixed Income Markets? Theory and Evidence for Unspanned Stochastic Volatility," Journal of Finance, American Finance Association, vol. 57(4), pages 1685-1730, August.
    7. de Jong, C.M., 2005. "The Nature of Power Spikes: a regime-switch approach," ERIM Report Series Research in Management ERS-2005-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Levy, Moshe & Ritov, Yaacov, 2001. "Portfolio Optimization with Many Assets: The Importance of Short-Selling," University of California at Los Angeles, Anderson Graduate School of Management qt41x4t67m, Anderson Graduate School of Management, UCLA.
    9. Enlin Pan & Liuren Wu, 2006. "Taking Positive Interest Rates Seriously," World Scientific Book Chapters, in: Cheng-Few Lee (ed.), Advances In Quantitative Analysis Of Finance And Accounting, chapter 14, pages 327-356, World Scientific Publishing Co. Pte. Ltd..
    10. Svenstrup, Mikkel, 2003. "On the Suboptimality of Single-Factor Exercise Strategies for Bermudan Swaptions," Finance Working Papers 02-24, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    11. Francis A. Longstaff, 2004. "Optimal Recursive Refinancing and the Valuation of Mortgage-Backed Securities," NBER Working Papers 10422, National Bureau of Economic Research, Inc.
    12. Svenstrup, Mikkel, 2005. "On the suboptimality of single-factor exercise strategies for Bermudan swaptions," Journal of Financial Economics, Elsevier, vol. 78(3), pages 651-684, December.
    13. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    14. Grzegorz Krzy.zanowski & Marcin Magdziarz, 2020. "A computational weighted finite difference method for American and barrier options in subdiffusive Black-Scholes model," Papers 2003.05358, arXiv.org, revised Dec 2020.
    15. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, June.
    16. Christophe PÉRIGNON & Christophe VILLA, 2002. "Permanent and Transitory Factors Affecting the Dynamics of the Term Structure of Interest Rates," FAME Research Paper Series rp53, International Center for Financial Asset Management and Engineering.
    17. Couch, Robert & Wu, Wei, 2016. "The fair value option for liabilities and stock returns during the financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 83-98.
    18. Chockalingam, Arun & Feng, Haolin, 2015. "The implication of missing the optimal-exercise time of an American option," European Journal of Operational Research, Elsevier, vol. 243(3), pages 883-896.
    19. Jensen, Malene Shin & Svenstrup, Mikkel, 2002. "Efficient Control Variates and Strategies for Bermudan Swaptions in a Libor Market Model," Finance Working Papers 02-23, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    20. Ferdinando Ametrano & Mark Joshi, 2011. "Smooth simultaneous calibration of the LMM to caplets and co-terminal swaptions," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 547-558.
    21. Damir Filipovic & Yerkin Kitapbayev, 2016. "On the American swaption in the linear-rational framework," Papers 1607.02067, arXiv.org, revised Feb 2018.
    22. De Jong Cyriel, 2006. "The Nature of Power Spikes: A Regime-Switch Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-28, September.
    23. Victor Lapshin & Marat Kurbangaleev, 2013. "A joint non-parametric approach to the decomposition of bond yields and CDS spreads: application of Eurozone market data," HSE Working papers WP BRP 13/FE/2013, National Research University Higher School of Economics.
    24. de Jong, C.M. & Huisman, R., 2002. "Option Formulas for Mean-Reverting Power Prices with Spikes," ERIM Report Series Research in Management ERS-2002-96-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    25. Dariusz Gatarek & Juliusz Jabłecki, 2021. "Between Scylla and Charybdis: The Bermudan Swaptions Pricing Odyssey," Mathematics, MDPI, vol. 9(2), pages 1-32, January.
    26. Bueno-Guerrero, Alberto & Moreno, Manuel & Navas, Javier F., 2020. "Valuation of caps and swaptions under a stochastic string model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).

  19. de Jong, Frank & Santa-Clara, Pedro, 1999. "The Dynamics of the Forward Interest Rate Curve: A Formulation with State Variables," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(1), pages 131-157, March.

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    1. Haitao Li & Xiaoxia Ye, 2013. "A Type of HJM Based Affine Model: Theory and Empirical Evidence," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    2. Francis X. Diebold & Canlin Li, 2002. "Forecasting the Term Structure of Government Bond Yields," Center for Financial Institutions Working Papers 02-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. Dempster, M.A.H. & Tang, Ke, 2011. "Estimating exponential affine models with correlated measurement errors: Applications to fixed income and commodities," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 639-652, March.
    4. De Rossi, Giuliano, 2004. "Kalman filtering of consistent forward rate curves: a tool to estimate and model dynamically the term structure," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 277-308, March.
    5. Buraschi, Andrea & Corielli, Francesco, 2005. "Risk management implications of time-inconsistency: Model updating and recalibration of no-arbitrage models," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2883-2907, November.
    6. Lioui, Abraham & Poncet, Patrice, 2003. "International asset allocation: A new perspective," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2203-2230, November.
    7. Francis X. Diebold, 2004. "The Nobel Memorial Prize for Robert F. Engle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 106(2), pages 165-185, June.
    8. Andrea Gombani & Wolfgang J. Runggaldier, 2001. "A Filtering Approach To Pricing In Multifactor Term Structure Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 4(02), pages 303-320.
    9. Andrew Jeffrey & Linton, Oliver Linton & Thong Nguyen & Peter C.B. Phillips, 2001. "Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach," Cowles Foundation Discussion Papers 1311, Cowles Foundation for Research in Economics, Yale University.
    10. Cortazar, Gonzalo & Schwartz, Eduardo S. & Naranjo, Lorezo, 2003. "Term Structure Estimation in Low-Frequency Transaction Markets: A Kalman Filter Approach with Incomplete Panel-Data," University of California at Los Angeles, Anderson Graduate School of Management qt56h775cz, Anderson Graduate School of Management, UCLA.
    11. Baaquie, Belal E. & Pan, Tang, 2011. "Simulation of coupon bond European and barrier options in quantum finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 263-289.
    12. Renne, J-P., 2009. "Frequency-domain analysis of debt service in a macro-finance model for the euro area," Working papers 261, Banque de France.
    13. Anders B. Trolle & Eduardo S. Schwartz, 2009. "A General Stochastic Volatility Model for the Pricing of Interest Rate Derivatives," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 2007-2057, May.
    14. Falini, Jury, 2010. "Pricing caps with HJM models: The benefits of humped volatility," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1358-1367, December.
    15. Carl Chiarella & Hing Hung & Thuy-Duong To, 2005. "The Volatility Structure of the Fixed Income Market under the HJM Framework: A Nonlinear Filtering Approach," Research Paper Series 151, Quantitative Finance Research Centre, University of Technology, Sydney.
    16. Carl Chiarella & Oh-Kang Kwon, 2000. "A Complete Stochastic Volatility Model in the HJM Framework," Research Paper Series 43, Quantitative Finance Research Centre, University of Technology, Sydney.
    17. 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.
    18. Luca Benati, 2006. "Affine term structure models for the foreign exchange risk premium," Bank of England working papers 291, Bank of England.
    19. Gonzalo Cortazar & Eduardo S. Schwartz & Lorenzo F. Naranjo, 2007. "Term-structure estimation in markets with infrequent trading," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 353-369.
    20. Antje Berndt & Peter Ritchken & Zhiqiang Sun, 2010. "On Correlation and Default Clustering in Credit Markets," The Review of Financial Studies, Society for Financial Studies, vol. 23(7), pages 2680-2729, July.
    21. Gombani, Andrea & Jaschke, Stefan R. & Runggaldier, Wolfgang J., 2005. "A filtered no arbitrage model for term structures from noisy data," Stochastic Processes and their Applications, Elsevier, vol. 115(3), pages 381-400, March.
    22. Carl Chiarella & Oh Kwon, 2003. "Finite Dimensional Affine Realisations of HJM Models in Terms of Forward Rates and Yields," Review of Derivatives Research, Springer, vol. 6(2), pages 129-155, May.
    23. Ramaprasad Bhar, 2010. "Stochastic Filtering with Applications in Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736, June.
    24. Power, Gabriel J. & Turvey, Calum G., 2008. "On Term Structure Models of Commodity Futures Prices and the Kaldor-Working Hypothesis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37608, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    25. Ram Bhar & Carl Chiarella & Thuy Duong To, 2002. "A Maximum Likelihood Approach to Estimation of Heath-Jarrow-Morton Models," Research Paper Series 80, Quantitative Finance Research Centre, University of Technology, Sydney.
    26. Wolfgang Lemke & Deutsche Bundesbank, 2006. "Term Structure Modeling and Estimation in a State Space Framework," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-28344-7, October.
    27. Jury Falini, 2009. "Pricing caps with HJM models: the benefits of humped volatility," Department of Economics University of Siena 563, Department of Economics, University of Siena.
    28. Michael A H Dempster & Elena A Medova & Michael Villaverde, 2010. "Long-term interest rates and consol bond valuation," Journal of Asset Management, Palgrave Macmillan, vol. 11(2), pages 113-135, June.
    29. Longstaff, Francis A & Santa-Clara, Pedro & Schwartz, Eduardo S, 2000. "The Relative Valuation of Caps and Swaptions: Theory and Empirical Evidence," University of California at Los Angeles, Anderson Graduate School of Management qt65f1914p, Anderson Graduate School of Management, UCLA.
    30. Chiara Sabelli & Michele Pioppi & Luca Sitzia & Giacomo Bormetti, 2014. "Multi-curve HJM modelling for risk management," Papers 1411.3977, arXiv.org, revised Oct 2015.
    31. Choong Tze Chua & Dean Foster & Krishna Ramaswamy & Robert Stine, 2008. "A Dynamic Model for the Forward Curve," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 265-310, January.
    32. Li, Haitao & Ye, Xiaoxia & Yu, Fan, 2020. "Unifying Gaussian dynamic term structure models from a Heath–Jarrow–Morton perspective," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1153-1167.
    33. Giuliano De Rossi, 2004. "Maximum likelihood estimation of the Cox-Ingersoll-Ross model using particle filters," Computing in Economics and Finance 2004 302, Society for Computational Economics.
    34. Christina Nikitopoulos-Sklibosios, 2005. "A Class of Markovian Models for the Term Structure of Interest Rates Under Jump-Diffusions," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2005.
    35. Andrew Jeffrey, 2004. "Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 251-289.
    36. Lioui, Abraham & Poncet, Patrice, 2002. "Optimal currency risk hedging," Journal of International Money and Finance, Elsevier, vol. 21(2), pages 241-264, April.
    37. Casassus, Jaime & Collin-Dufresne, Pierre & Goldstein, Bob, 2005. "Unspanned stochastic volatility and fixed income derivatives pricing," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2723-2749, November.
    38. Duffie, Darrell, 2003. "Intertemporal asset pricing theory," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 11, pages 639-742, Elsevier.

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