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Rossen Valkanov

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. 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.

    Cited by:

    1. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.

  2. Rossen Valkanov & Andra Ghent, 2014. "Complexity in Structured Finance: Financial Wizardry or Smoke and Mirrors," 2014 Meeting Papers 104, Society for Economic Dynamics.

    Cited by:

    1. Célérier, Claire & Vallée, Boris, 2016. "Catering to investors through product complexity," ESRB Working Paper Series 14, European Systemic Risk Board.
    2. Marco Bardoscia & Daniele d'Arienzo & Matteo Marsili & Valerio Volpati, 2019. "Lost in Diversification," Papers 1901.09795, arXiv.org.
    3. Xudong An & Yongheng Deng & Joseph Nichols & Anthony Sanders, 2015. "What is Subordination About? Credit Risk and Subordination Levels in Commercial Mortgage-backed Securities (CMBS)," The Journal of Real Estate Finance and Economics, Springer, vol. 51(2), pages 231-253, August.
    4. Chen, Zhizhen & Liu, Frank Hong & Opong, Kwaku & Zhou, Mingming, 2017. "Short-term safety or long-term failure? Empirical evidence of the impact of securitization on bank risk," Journal of International Money and Finance, Elsevier, vol. 72(C), pages 48-74.
    5. Arnold, Marc & Schuette, Dustin & Wagner, Alexander, 2014. "Neglected Risk: Evidence from Structured Product Counterparty Exposure," Working Papers on Finance 1406, University of St. Gallen, School of Finance, revised Apr 2016.
    6. Sareh Pouryousefi & Jeff Frooman, 2019. "The Consumer Scam: An Agency-Theoretic Approach," Journal of Business Ethics, Springer, vol. 154(1), pages 1-12, January.

  3. Davide Pettenuzzo & Allan Timmermann & Rossen Valkanov, 2013. "Forecasting Stock Returns under Economic Constraints," Working Papers 57, Brandeis University, Department of Economics and International Business School.

    Cited by:

    1. 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.
    2. 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.
    3. Prabhu Prasad Panda & Maysam Khodayari Gharanchaei & Xilin Chen & Haoshu Lyu, 2024. "Application of Deep Learning for Factor Timing in Asset Management," Papers 2404.18017, arXiv.org.
    4. Oh, Dong Hwan & Patton, Andrew J., 2024. "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, vol. 242(1).
    5. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    6. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    7. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    8. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    9. 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.
    10. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    11. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    12. 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).
    13. David E. Rapach & Matthew C. Ringgenberg & Guofu Zhou, 2016. "Short interest and aggregate stock returns," CEMA Working Papers 716, China Economics and Management Academy, Central University of Finance and Economics.
    14. Smith, Simon C., 2017. "Equity premium estimates from economic fundamentals under structural breaks," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 49-61.
    15. Timmermann, Allan & Pettenuzzo, Davide & Gargano, Antonio, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," CEPR Discussion Papers 10104, C.E.P.R. Discussion Papers.
    16. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    17. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    18. Carlos Carvalho & Jared D. Fisher & Davide Pettenuzzo, 2018. "Optimal Asset Allocation with Multivariate Bayesian Dynamic Linear Models," Working Papers 123, Brandeis University, Department of Economics and International Business School.
    19. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    20. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    21. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    22. Chenchen Li & Chongfeng Wu & Chunyang Zhou, 2021. "Forecasting equity returns: The role of commodity futures along the supply chain," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 46-71, January.
    23. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116, Brandeis University, Department of Economics and International Business School.
    24. 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.).
    25. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    26. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    27. Kenechukwu E. Anadu & James Bohn & Lina Lu & Matthew Pritsker & Andrei Zlate, 2019. "Reach for Yield by U.S. Public Pension Funds," Finance and Economics Discussion Series 2019-048, Board of Governors of the Federal Reserve System (U.S.).
    28. Biao Guo & Qian Han & Hai Lin, 2018. "Are there gains from using information over the surface of implied volatilities?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 645-672, June.
    29. 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.
    30. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
    31. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    32. 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.
    33. 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.
    34. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    35. Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
    36. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
    37. de Oliveira Souza, Thiago, 2019. "Predictability concentrates in bad times. And so does disagreement," Discussion Papers on Economics 8/2019, University of Southern Denmark, Department of Economics.
    38. Coqueret, Guillaume & Deguest, Romain, 2024. "Unexpected opportunities in misspecified predictive regressions," European Journal of Operational Research, Elsevier, vol. 318(2), pages 686-700.
    39. Afees A. Salisu & Raymond Swaray & Tirimisyu F. Oloko, 2017. "A multi-factor predictive model for oil-US stock nexus with persistence, endogeneity and conditional heteroscedasticity effects," Working Papers 024, Centre for Econometric and Allied Research, University of Ibadan.
    40. Li Liu & Zhiyuan Pan & Yudong Wang, 2022. "Shrinking return forecasts," The Financial Review, Eastern Finance Association, vol. 57(3), pages 641-661, August.
    41. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    42. Chiara Limongi Concetto & Francesco Ravazzolo, 2019. "Optimism in Financial Markets: Stock Market Returns and Investor Sentiments," BEMPS - Bozen Economics & Management Paper Series BEMPS56, Faculty of Economics and Management at the Free University of Bozen.
    43. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    44. Xianfeng Hao & Yudong Wang, 2023. "Forecasting the stock risk premium: A new statistical constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1805-1822, November.
    45. Guillaume Coqueret & Romain Deguest, 2024. "Unexpected opportunities in misspecified predictive regressions," Post-Print hal-04595355, HAL.
    46. Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).
    47. 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.
    48. Gonçalo Faria & Fabio Verona, 2017. "Forecasting stock market returns by summing the frequency-decomposed parts," CEF.UP Working Papers 1702, Universidade do Porto, Faculdade de Economia do Porto.
    49. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    50. 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.
    51. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    52. Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo MM & Taylor, AM Robert, 2022. "Extensions to IVX Methods of Inference for Return Predictability," Essex Finance Centre Working Papers 29779, University of Essex, Essex Business School.
    53. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    54. Andrew Detzel & Hong Liu & Jack Strauss & Guofu Zhou & Yingzi Zhu, 2021. "Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals," Financial Management, Financial Management Association International, vol. 50(1), pages 107-137, March.
    55. 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.
    56. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    57. 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.
    58. 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.
    59. 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.
    60. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    61. Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
    62. Sha Zhu & Fujun Lai & Jie Deng & Qian Wang, 2021. "Do Mutual Funds’ Exposure to Financial Stress Predict Their Future Returns? Evidence From China," SAGE Open, , vol. 11(4), pages 21582440211, October.
    63. Lin, Hai & Tao, Xinyuan & Wu, Chunchi, 2022. "Forecasting earnings with combination of analyst forecasts," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 133-159.
    64. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    65. Bai, Fan & Zhang, Yaqi & Chen, Zhonglu & Li, Yan, 2023. "The volatility of daily tug-of-war intensity and stock market returns," Finance Research Letters, Elsevier, vol. 55(PA).
    66. 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.
    67. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    68. Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    69. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    70. Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
    71. Antonios K. Alexandridis & Ekaterini Panopoulou & Ioannis Souropanis, 2024. "Forecasting exchange rates: An iterated combination constrained predictor approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 983-1017, July.
    72. Ma, Feng & Wu, Hanlin & Zeng, Qing, 2024. "Biodiversity and stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    73. 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.
    74. 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.
    75. 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.
    76. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    77. Rojo Suárez, Javier & Alonso Conde, Ana Belén & Ferrero Pozo, Ricardo, 2020. "European equity markets: Who is the truly representative investor?," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 325-346.
    78. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    79. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    80. Mete Kilic & Ivan Shaliastovich, 2019. "Good and Bad Variance Premia and Expected Returns," Management Science, INFORMS, vol. 67(6), pages 2522-2544, June.
    81. 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.
    82. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    83. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    84. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Variance swap payoffs, risk premia and extreme market conditions," Econometrics and Statistics, Elsevier, vol. 13(C), pages 106-124.
    85. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    86. 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.
    87. 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.
    88. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
    89. Liu, Li & Bu, Ruijun & Pan, Zhiyuan & Xu, Yuhua, 2019. "Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test," Economic Modelling, Elsevier, vol. 81(C), pages 124-135.
    90. Dai, Zhifeng & Zhu, Huan, 2021. "Indicator selection and stock return predictability," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    91. 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.
    92. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    93. Michaelides, Alexander & Zhang, Yuxin, 2022. "Life-cycle portfolio choice with imperfect predictors," Journal of Banking & Finance, Elsevier, vol. 135(C).
    94. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    95. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    96. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.
    97. Sun, Yuzhe & Wang, Yanjie & Zhang, Shunming & Huang, Helen, 2023. "The impact of ambiguity-loving attitude on market participation and asset pricing," Economic Modelling, Elsevier, vol. 128(C).
    98. 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).
    99. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    100. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    101. 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).
    102. Kocaarslan, Baris & Sari, Ramazan & Gormus, Alper & Soytas, Ugur, 2017. "Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 41-56.
    103. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    104. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2018. "Forecasting the prices of crude oil using the predictor, economic and combined constraints," Economic Modelling, Elsevier, vol. 75(C), pages 237-245.
    105. Qian, Lihua & Zeng, Qing & Lu, Xinjie & Ma, Feng, 2022. "Global tail risk and oil return predictability," Finance Research Letters, Elsevier, vol. 47(PB).
    106. Zhang, Xincheng, 2024. "Country-level energy-related uncertainties and stock market returns: Insights from the U.S. and China," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    107. Scott Cederburg & Travis L Johnson & Michael S O’Doherty, 2023. "On the Economic Significance of Stock Return Predictability," Review of Finance, European Finance Association, vol. 27(2), pages 619-657.
    108. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    109. Zhang, Yaojie & Wei, Yu & Ma, Feng & Yi, Yongsheng, 2019. "Economic constraints and stock return predictability: A new approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 1-9.
    110. Mauro Bernardi & Daniele Bianchi & Nicolas Bianco, 2022. "Variational inference for large Bayesian vector autoregressions," Papers 2202.12644, arXiv.org, revised Jun 2023.
    111. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    112. Nima Nonejad, 2021. "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, vol. 61(2), pages 973-1009, August.
    113. Liu, Li & Pan, Zhiyuan, 2020. "Forecasting stock market volatility: The role of technical variables," Economic Modelling, Elsevier, vol. 84(C), pages 55-65.
    114. Procasky, William J. & Yin, Anwen, 2023. "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    115. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    116. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    117. 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).
    118. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    119. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    120. 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.
    121. Jiawen Xu & Pierre Perron, 2023. "Forecasting in the presence of in-sample and out-of-sample breaks," Empirical Economics, Springer, vol. 64(6), pages 3001-3035, June.
    122. 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.
    123. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    124. 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.
    125. Daniele Bianchi & Massimo Guidolin & Manuela Pedio, 2020. "Dissecting Time-Varying Risk Exposures in Cryptocurrency Markets," BAFFI CAREFIN Working Papers 20143, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    126. Zhifeng Dai & Jie Kang & Hua Yin, 2023. "Forecasting equity risk premium: A new method based on wavelet de‐noising," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4331-4352, October.
    127. 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).
    128. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    129. Yu, Fanchao, 2023. "Macroeconomic information, global economic policy uncertainty and gold futures return predictability," Finance Research Letters, Elsevier, vol. 55(PA).
    130. Procasky, William J. & Yin, Anwen, 2023. "Identifying the true nature of price discovery and cross-market informational flow in the investment grade CDS and equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
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    1. 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.

  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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    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).
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    4. 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.
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    6. 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.
    7. 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.
    8. 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.
    9. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
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    12. 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.
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    1. 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.
    2. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
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    4. 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.
    5. 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.
    6. 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.
    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. 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.
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    13. Dhaoui, Abderrazak & Khraief, Naceur, 2014. "Empirical linkage between oil price and stock market returns and volatility: Evidence from international developed markets," Economics Discussion Papers 2014-12, Kiel Institute for the World Economy (IfW Kiel).
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    17. Ferreira, Paulo & Pereira, Éder Johson de Area Leão & Silva, Marcus Fernandes da & Pereira, Hernane Borges, 2019. "Detrended correlation coefficients between oil and stock markets: The effect of the 2008 crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 86-96.
    18. Lee, Bong-Soo & Rui, Oliver Meng & Wang, Steven Shuye, 2004. "Information transmission between the NASDAQ and Asian second board markets," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1637-1670, July.
    19. Dhaoui, Abderrazak & Saidi, Youssef, 2015. "Oil supply and demand shocks and stock price: Evidence for some OECD countries," MPRA Paper 63556, University Library of Munich, Germany.

  10. Jose Tavares & Rossen Valkanov, 2001. "The neglected effect of fiscal policy on stock and bond returns," Nova SBE Working Paper Series wp413, Universidade Nova de Lisboa, Nova School of Business and Economics.

    Cited by:

    1. Agnello, Luca & Castro, Vítor & Sousa, Ricardo M., 2012. "How does fiscal policy react to wealth composition and asset prices?," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 874-890.
    2. Chiwei Su & Yiru Liu & Chang Liu & Ran Tao, 2022. "The Impact of Medical and Health Fiscal Expenditures on Pharmaceutical Industry Stock Index in China," IJERPH, MDPI, vol. 19(18), pages 1-14, September.
    3. Rangan Gupta & Chi Keung Marco Lau & Stephen M. Miller & Mark E. Wohar, 2017. "U.S. Fiscal Policy and Asset Prices: The Role of Partisan Conflict," Working Papers 201742, University of Pretoria, Department of Economics.
    4. Ghassen El Montasser & Rangan Gupta & Charl Jooste & Stephen M. Miller, 2015. "The Time-Series Linkages between US Fiscal Policy and Asset Prices," Working Papers 201519, University of Pretoria, Department of Economics.
    5. Luca Agnello & Davide Furceri & Ricardo M. Sousa, 2011. "Fiscal Policy Discretion, Private Spending, and Crisis Episodes," NIPE Working Papers 31/2011, NIPE - Universidade do Minho.
    6. Kofi A. Amoateng, 2019. "Did Tom Brady Save the US stock market? Market Anomaly or Market Efficiency?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(5), pages 128-128, May.
    7. Rangan Gupta & Charl Jooste & Kanyane Matlou, 2013. "A Time-Varying Approach to Analysing Fiscal Policy and Asset Prices in South Africa," Working Papers 201303, University of Pretoria, Department of Economics.
    8. Arin, K. Peren & Mamun, Abdullah & Purushothman, Nanda, 2009. "The effects of tax policy on financial markets: G3 evidence," Review of Financial Economics, Elsevier, vol. 18(1), pages 33-46, January.
    9. Terezie Lokajickova, 2010. "Could the Stability and Growth Pact Be Substituted by the Financial Markets?," Working Papers IES 2010/30, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2010.
    10. Pasquale Foresti & Oreste Napolitano, 2016. "On the Stock Markets’ Reactions to Taxation and Public Expenditure," LEQS – LSE 'Europe in Question' Discussion Paper Series 115, European Institute, LSE.
    11. Luca Agnello & Davide Furceri & Ricardo Sousa, 2013. "Discretionary Government Consumption, Private Domestic Demand, and Crisis Episodes," Open Economies Review, Springer, vol. 24(1), pages 79-100, February.
    12. Alexander Zimper, 2014. "The minimal confidence levels of Basel capital regulation," Journal of Banking Regulation, Palgrave Macmillan, vol. 15(2), pages 129-143, April.
    13. Ardagna Silvia & Caselli Francesco & Lane Timothy, 2007. "Fiscal Discipline and the Cost of Public Debt Service: Some Estimates for OECD Countries," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-35, August.
    14. Ardagna, Silvia & Caselli, Francesco & Lane, Timothy, 2005. "Fiscal discipline and the cost of public debt service: some estimates for OECD countries," LSE Research Online Documents on Economics 3562, London School of Economics and Political Science, LSE Library.
    15. Hardik A. Marfatia & Rangan Gupta & Stephen M. Miller, 2020. "125 Years of Time-Varying Effects of Fiscal Policy on Financial Markets," Working papers 2020-12, University of Connecticut, Department of Economics.
    16. Ardagna, Silvia, 2009. "Financial markets' behavior around episodes of large changes in the fiscal stance," European Economic Review, Elsevier, vol. 53(1), pages 37-55, January.
    17. Luca Agnello & Gilles Dufrénot & Ricardo M. Sousa, 2012. "Adjusting the U.S. Fiscal Policy for Asset Prices: Evidence from a TVP-MS Framework," NIPE Working Papers 20/2012, NIPE - Universidade do Minho.
    18. Anthony M. Diercks & William Waller, 2017. "Taxes and the Fed : Theory and Evidence from Equities," Finance and Economics Discussion Series 2017-104, Board of Governors of the Federal Reserve System (U.S.).
    19. Mr. Sanjeev Gupta & Mr. Carlos Mulas-Granados & Mr. Emanuele Baldacci, 2009. "How Effective is Fiscal Policy Response in Systemic Banking Crises?," IMF Working Papers 2009/160, International Monetary Fund.
    20. BUI, Duy-Tung & LLORCA, Matthieu & BUI, Thi Mai Hoai, 2018. "Dynamics between stock market movements and fiscal policy: Empirical evidence from emerging Asian economies," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 65-74.
    21. Marfatia, Hardik A. & Gupta, Rangan & Miller, Stephen, 2020. "125 ​Years of time-varying effects of fiscal policy on financial markets," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 303-320.
    22. Taha, Roshaiza & Colombage, Sisira R.N. & Maslyuk, Svetlana & Nanthakumar, Loganathan, 2013. "Does financial system activity affect tax revenue in Malaysia? Bounds testing and causality approach," Journal of Asian Economics, Elsevier, vol. 24(C), pages 147-157.
    23. Narayan Sethi & Saileja Mohanty & Sanhita Sucharita & Nanthakumar Loganathan, 2020. "Tax Reform And Economic Growth Nexus In India: Evidence From The Cointegration And Rolling-Window Causality," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(06), pages 1699-1725, December.

  11. Torous, Walter & Valkanov, Rossen, 2000. "Boundaries of Predictability: Noisy Predictive Regressions," University of California at Los Angeles, Anderson Graduate School of Management qt33p7672z, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Kim, Chang Sik & Lee, Sungro, 2011. "Spurious regressions driven by excessive volatility," Economics Letters, Elsevier, vol. 113(3), pages 292-297.
    2. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
    3. Shang, Hua, 2013. "Inference in asset pricing models with a low-variance factor," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1046-1060.
    4. Todd E. Clark & Michael W. McCracken, 2009. "In-sample tests of predictive ability: a new approach," Research Working Paper RWP 09-10, Federal Reserve Bank of Kansas City.
    5. Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
    6. Ravi Bansal & Varoujan Khatchatrian & Amir Yaron, 2004. "Interpretable Asset Markets?," 2004 Meeting Papers 136b, Society for Economic Dynamics.
    7. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    8. Yufeng Han, 2010. "On the Economic Value of Return Predictability," Annals of Economics and Finance, Society for AEF, vol. 11(1), pages 1-33, May.
    9. Phillips, Peter C.B. & Lee, Ji Hyung, 2013. "Predictive regression under various degrees of persistence and robust long-horizon regression," Journal of Econometrics, Elsevier, vol. 177(2), pages 250-264.
    10. Alois Weigand, 2019. "Machine learning in empirical asset pricing," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 93-104, March.
    11. Deng, Kaihua, 2016. "A refined asymptotic framework for dividend yield in predictive regressions," Economics Letters, Elsevier, vol. 138(C), pages 60-63.
    12. Robert D. Arnott & Jason C. Hsu & Jun Liu & Harry Markowitz, 2015. "Can Noise Create the Size and Value Effects?," Management Science, INFORMS, vol. 61(11), pages 2569-2579, November.
    13. Peter C. B. Phillips, 2015. "Halbert White Jr. Memorial JFEC Lecture: Pitfalls and Possibilities in Predictive Regression†," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 521-555.
    14. 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.

  12. Valkanov, Rossen, 1999. "The Term Structure with Highly Persistent Interest Rates," University of California at Los Angeles, Anderson Graduate School of Management qt8x91m4hg, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Lanne, Markku, 1999. "Testing the expectations hypothesis of the term structure of interest rates in the presence of a potential regime shift," Bank of Finland Research Discussion Papers 20/1999, Bank of Finland.
    2. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.

  13. Valkanov, Rossen, 1999. "Equity Premium and Dividend Yield regressions: A lot of noise, little information, confusing results," University of California at Los Angeles, Anderson Graduate School of Management qt955135m1, Anderson Graduate School of Management, UCLA.

    Cited by:

    1. Valkanov, Rossen, 1999. "Long-Horizon Regressions: Theoretical Results and Applications to the Expected Returns/Dividend Yields and Fisher Effect Relations," University of California at Los Angeles, Anderson Graduate School of Management qt67b2h2gb, Anderson Graduate School of Management, UCLA.

Articles

  1. Eric Ghysels & Alberto Plazzi & Rossen Valkanov & Antonio Rubia & Asad Dossani, 2019. "Direct Versus Iterated Multiperiod Volatility Forecasts," Annual Review of Financial Economics, Annual Reviews, vol. 11(1), pages 173-195, December.

    Cited by:

    1. Chronopoulos, Ilias & Raftapostolos, Aristeidis & Kapetanios, George, 2023. "Forecasting Value-at-Risk using deep neural network quantile regression," Essex Finance Centre Working Papers 34837, University of Essex, Essex Business School.
    2. 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.
    3. Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
    4. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    5. O-Chia Chuang & Rangan Gupta & Christian Pierdzioch & Buliao Shu, 2024. "Financial Uncertainty and Gold Market Volatility: Evidence from a GARCH-MIDAS Approach with Variable Selection," Working Papers 202441, University of Pretoria, Department of Economics.
    6. Ewald, Christian & Hadina, Jelena & Haugom, Erik & Lien, Gudbrand & Størdal, Ståle & Yahya, Muhammad, 2023. "Sample frequency robustness and accuracy in forecasting Value-at-Risk for Brent Crude Oil futures," Finance Research Letters, Elsevier, vol. 58(PA).
    7. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.
    8. Salisu, Afees A. & Gupta, Rangan & Demirer, Riza, 2022. "Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model," Energy Economics, Elsevier, vol. 108(C).
    9. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024. "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 280-293.
    10. 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).
    11. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    12. Papantonis Ioannis & Rompolis Leonidas S. & Tzavalis Elias & Agapitos Orestis, 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    13. González-Pla, Francisco & Lovreta, Lidija, 2022. "Modeling and forecasting firm-specific volatility: The role of asymmetry and long-memory," Finance Research Letters, Elsevier, vol. 48(C).
    14. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    15. Dossani, Asad, 2024. "Monetary policy and currency variance risk premia," Research in International Business and Finance, Elsevier, vol. 69(C).
    16. Ye-Ji Seo & Sunggon Kim, 2024. "A Sequential Importance Sampling for Estimating Multi-Period Tail Risk," Risks, MDPI, vol. 12(12), pages 1-22, December.
    17. Afees A. Salisu & Ahamuefula E.Oghonna & Rangan Gupta & Oguzhan Cepni, 2024. "Energy Market Uncertainties and US State-Level Stock Market Volatility: A GARCH-MIDAS Approach," Working Papers 202409, University of Pretoria, Department of Economics.
    18. Afees A. Salisu & Ahamuefula E. Ogbonna & Elie Bouri & Rangan Gupta, 2024. "Economic Policy Uncertainty and Bank-Level Stock Returns Volatility of the United States: A Mixed-Frequency Perspective," Working Papers 202444, University of Pretoria, Department of Economics.

  2. Andra Ghent & Rossen Valkanov, 2016. "Comparing Securitized and Balance Sheet Loans: Size Matters," Management Science, INFORMS, vol. 62(10), pages 2784-2803, October.

    Cited by:

    1. David P. Glancy & Robert J. Kurtzman & Lara Loewenstein, 2022. "Loan Modifications and the Commercial Real Estate Market," Working Papers 22-09, Federal Reserve Bank of Cleveland.
    2. David Downs & Pisun (Tracy) Xu, 2015. "Commercial Real Estate, Distress and Financial Resolution: Portfolio Lending Versus Securitization," The Journal of Real Estate Finance and Economics, Springer, vol. 51(2), pages 254-287, August.
    3. Xudong An & Lawrence R. Cordell & Nicholas Smith, 2023. "CMBS Market Evolution and Emerging Risks," Working Papers 23-27, Federal Reserve Bank of Philadelphia.
    4. Reher, Michael, 2021. "Finance and the supply of housing quality," Journal of Financial Economics, Elsevier, vol. 142(1), pages 357-376.
    5. Martin Hibbeln & Werner Osterkamp, 2024. "Simple is simply not enough—features versus labels of complex financial securities," Review of Derivatives Research, Springer, vol. 27(2), pages 113-150, July.
    6. David P. Glancy & John Krainer & Robert J. Kurtzman & Joseph B. Nichols, 2019. "Intermediary Segmentation in the Commercial Real Estate Market," Finance and Economics Discussion Series 2019-079, Board of Governors of the Federal Reserve System (U.S.).
    7. Hibbeln, Martin & Osterkamp, Werner, 2024. "The Impact of Risk Retention on Moral Hazard in the Securitization Market," Journal of Banking & Finance, Elsevier, vol. 163(C).
    8. Lamont K. Black & John Krainer & Joseph B. Nichols, 2017. "Safe Collateral, Arm’s-Length Credit: Evidence from the Commercial Real Estate Market," Working Paper Series 2017-19, Federal Reserve Bank of San Francisco.

  3. 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.

    Cited by:

    1. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    2. 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.
    3. 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.
    4. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
    5. 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.
    6. Özgür Ömer Ersin & Melike Bildirici, 2023. "Financial Volatility Modeling with the GARCH-MIDAS-LSTM Approach: The Effects of Economic Expectations, Geopolitical Risks and Industrial Production during COVID-19," Mathematics, MDPI, vol. 11(8), pages 1-26, April.
    7. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    8. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    9. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
    10. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    11. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    12. 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.
    13. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    14. 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.
    15. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    16. 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).
    17. 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.
    18. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    19. Mei, Dexiang & Zhao, Chenchen & Luo, Qin & Li, Yan, 2022. "Forecasting the Chinese low-carbon index volatility," Resources Policy, Elsevier, vol. 77(C).
    20. 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.
    21. 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.
    22. Morita, Hiroshi, 2022. "Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach," Discussion paper series HIAS-E-118, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    23. 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.
    24. Ana Beatriz Galvão & Marta Lopresto, 2020. "Real-time Probabilistic Nowcasts of UK Quarterly GDP Growth using a Mixed-Frequency Bottom-up Approach," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-06, Economic Statistics Centre of Excellence (ESCoE).
    25. Ding, Shusheng & Zheng, Dandan & Cui, Tianxiang & Du, Min, 2023. "The oil price-inflation nexus: The exchange rate pass- through effect," Energy Economics, Elsevier, vol. 125(C).
    26. 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.
    27. Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
    28. Niko Hauzenberger & Massimiliano Marcellino & Michael Pfarrhofer & Anna Stelzer, 2024. "Nowcasting with Mixed Frequency Data Using Gaussian Processes," Papers 2402.10574, arXiv.org, revised Sep 2024.
    29. Kiss, Tamás & Österholm, Pär, 2020. "Fat tails in leading indicators," Economics Letters, Elsevier, vol. 193(C).
    30. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    31. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).
    32. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Monitoring daily unemployment at risk"," IREA Working Papers 202211, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    33. 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.

  4. Eric Ghysels & Alberto Plazzi & Rossen Valkanov, 2016. "Why Invest in Emerging Markets? The Role of Conditional Return Asymmetry," Journal of Finance, American Finance Association, vol. 71(5), pages 2145-2192, October.

    Cited by:

    1. Franzoni, Francesco & Ben-David, Itzhak & Moussawi, Rabih & Sedunov, John, 2019. "The Granular Nature of Large Institutional Investors," CEPR Discussion Papers 13427, C.E.P.R. Discussion Papers.
    2. Jozef Barun'ik & Matv{e}j Nevrla, 2018. "Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices," Papers 1806.06148, arXiv.org, revised Dec 2021.
    3. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
    4. Görtz, Christoph & Yeromonahos, Mallory, 2022. "Asymmetries in risk premia, macroeconomic uncertainty and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    5. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    6. 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).
    7. Canh P. Nguyen & Christophe Schinckus & Thanh D. Su & Felicia H. L. Chong, 2022. "Determinants of stock market returns in emerging markets: The linkage between institutional quality and macro liquidity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4472-4486, October.
    8. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2022. ""Daily Growth at Risk: financial or real drivers? The answer is not always the same"," IREA Working Papers 202208, University of Barcelona, Research Institute of Applied Economics, revised Jun 2022.
    9. 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.
    10. Chronopoulos, Ilias & Raftapostolos, Aristeidis & Kapetanios, George, 2023. "Forecasting Value-at-Risk using deep neural network quantile regression," Essex Finance Centre Working Papers 34837, University of Essex, Essex Business School.
    11. 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).
    12. Rita Pimentel & Morten Risstad & Sjur Westgaard, 2022. "Predicting interest rate distributions using PCA & quantile regression," Digital Finance, Springer, vol. 4(4), pages 291-311, December.
    13. Tsiakas, Ilias & Zhang, Haibin, 2021. "Economic fundamentals and the long-run correlation between exchange rates and commodities," Global Finance Journal, Elsevier, vol. 49(C).
    14. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2022. "Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    15. 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.
    16. 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.
    17. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    18. Jozef Barunik & Josef Kurka, 2021. "Risks of heterogeneously persistent higher moments," Papers 2104.04264, arXiv.org, revised Mar 2024.
    19. Yaojie Zhang & Qingxiang Han & Mengxi He, 2024. "Forecasting stock market returns with a lottery index: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1595-1606, August.
    20. Nicholas Apergis, 2022. "Evaluating tail risks for the U.S. economic policy uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3971-3989, October.
    21. Itzhak Ben-David & Francesco Franzoni & Byungwook Kim & Rabih Moussawi, 2021. "Competition for Attention in the ETF Space," NBER Working Papers 28369, National Bureau of Economic Research, Inc.
    22. Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
    23. Yang, Ann Shawing, 2020. "Misinformation corrections of corporate news: Corporate clarification announcements," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
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    52. Adam Farago & Erik Hjalmarsson, 2023. "Long-Horizon Stock Returns Are Positively Skewed," Review of Finance, European Finance Association, vol. 27(2), pages 495-538.
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    57. Ghysels, Eric & Liu, Hanwei, 2017. "Downside Risk in the Chinese Stock Market - Has it Fundamentally Changed?," CEPR Discussion Papers 12180, C.E.P.R. Discussion Papers.
    58. Zhou, Chunyang & Qin, Xiao, 2021. "Time-varying asymmetric tail dependence of international equities markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    59. 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.
    60. Lei, Likun & Shang, Yue & Chen, Yongfei & Wei, Yu, 2019. "Does the financial crisis change the economic risk perception of crude oil traders? A MIDAS quantile regression approach," Finance Research Letters, Elsevier, vol. 30(C), pages 341-351.
    61. Chen, Steven Shu-Hsiu, 2024. "International crash risk premium," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 94(C).
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    63. Tibor Szendrei & Arnab Bhattacharjee & Mark E. Schaffer, 2024. "MIDAS-QR with 2-Dimensional Structure," Papers 2406.15157, arXiv.org.
    64. Andrea Berardi & Michael Markovich & Alberto Plazzi & Andrea Tamoni, 2019. "Mind the (Convergence) Gap: Bond Predictability Strikes Back!," Swiss Finance Institute Research Paper Series 19-52, Swiss Finance Institute.
    65. Zhang, Hongwei & Zhao, Xinyi & Gao, Wang & Niu, Zibo, 2023. "The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models," Journal of Commodity Markets, Elsevier, vol. 32(C).
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    67. 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.
    68. Thiago Revil T. Ferreira, 2022. "Cross-Sectional Financial Conditions, Business Cycles and The Lending Channel," International Finance Discussion Papers 1335, Board of Governors of the Federal Reserve System (U.S.).
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  5. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2014. "Forecasting stock returns under economic constraints," Journal of Financial Economics, Elsevier, vol. 114(3), pages 517-553.
    See citations under working paper version above.
  6. Alberto Plazzi & Walter Torous & Rossen Valkanov, 2010. "Expected Returns and Expected Growth in Rents of Commercial Real Estate," The Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3469-3519.

    Cited by:

    1. Eirini Andriopoulou & Panagiotis Tsakloglou, 2011. "Once poor, always poor? Do initial conditions matter? Evidence from the ECHP," DEOS Working Papers 1127, Athens University of Economics and Business.
    2. Jim Clayton & David Ling & Andy Naranjo, 2009. "Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment," The Journal of Real Estate Finance and Economics, Springer, vol. 38(1), pages 5-37, January.
    3. John V. Duca & David C. Ling, 2015. "The other (commercial) real estate boom and bust: the effects of risk premia and regulatory capital arbitrage," Working Papers 1504, Federal Reserve Bank of Dallas.
    4. Renhe Liu & Eddie Chi-man Hui & Jiaqi Lv & Yi Chen, 2017. "What Drives Housing Markets: Fundamentals or Bubbles?," The Journal of Real Estate Finance and Economics, Springer, vol. 55(4), pages 395-415, November.
    5. Engsted, Tom & Pedersen, Thomas Q., 2015. "Predicting returns and rent growth in the housing market using the rent-price ratio: Evidence from the OECD countries," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 257-275.
    6. Timmermann, Allan & Møller, Stig & Pedersen, Thomas & Schütte, Erik Christian Montes, 2021. "Search and Predictability of Prices in the Housing Market," CEPR Discussion Papers 15875, C.E.P.R. Discussion Papers.
    7. Jack Corgel & Crocker Liu & Robert White, 2015. "Determinants of Hotel Property Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 51(3), pages 415-439, October.
    8. Ralph S.J. Koijen & Stijn Van Nieuwerburgh, 2011. "Predictability of Returns and Cash Flows," Annual Review of Financial Economics, Annual Reviews, vol. 3(1), pages 467-491, December.
    9. Zifeng Feng, 2022. "How Does Local Economy Affect Commercial Property Performance?," The Journal of Real Estate Finance and Economics, Springer, vol. 65(3), pages 361-383, October.
    10. Masud Alam, 2024. "Volatility in U.S. Housing Sector and the REIT Equity Return," The Journal of Real Estate Finance and Economics, Springer, vol. 69(3), pages 505-544, October.
    11. Cenedese, Gino & Mallucci, Enrico, 2015. "What moves international stock and bond markets?," LSE Research Online Documents on Economics 86296, London School of Economics and Political Science, LSE Library.
    12. Jarl G. Kallberg & Yoshiki Shimizu, 2023. "Acquisitions and the Opportunity Set," The Journal of Real Estate Finance and Economics, Springer, vol. 66(4), pages 904-938, May.
    13. Guglielmo Maria Caporale & Ricardo M. Sousa, 2011. "Consumption, Wealth, Stock and Housing Returns: Evidence from Emerging Markets," NIPE Working Papers 32/2011, NIPE - Universidade do Minho.
    14. Kraft, Holger & Munk, Claus & Weiss, Farina, 2019. "Predictors and portfolios over the life cycle," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 1-27.
    15. Joshua Gallin, 2008. "The Long‐Run Relationship Between House Prices and Rents," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 36(4), pages 635-658, December.
    16. Zongyuan Li & Rose Neng Lai, 2021. "Not All Bank Liquidity Creation Boosts Prices-The Case of the US Housing Market," International Real Estate Review, Global Social Science Institute, vol. 24(1), pages 19-58.
    17. Liu, Crocker H. & Rosenthal, Stuart S. & Strange, William C., 2018. "The vertical city: Rent gradients, spatial structure, and agglomeration economies," Journal of Urban Economics, Elsevier, vol. 106(C), pages 101-122.
    18. Engsted, Tom & Hviid, Simon J. & Pedersen, Thomas Q., 2016. "Explosive bubbles in house prices? Evidence from the OECD countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 14-25.
    19. Daisy J. HUANG & Charles Ka Yui LEUNG & Chung-Yi TSE, 2017. "What account for the differences in rent-price ratio and turnover rate? A search-and-matching approach," ISER Discussion Paper 0990, Institute of Social and Economic Research, Osaka University.
    20. Ellington, Michael & Fu, Xi & Zhu, Yunyi, 2023. "Real estate illiquidity and returns: A time-varying regional perspective," International Journal of Forecasting, Elsevier, vol. 39(1), pages 58-72.
    21. Dwight Jaffee & Richard Stanton & Nancy Wallace, 2019. "Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S," The Journal of Real Estate Finance and Economics, Springer, vol. 59(3), pages 329-371, October.
    22. Doina Chichernea & Norm Miller & Jeff Fisher & Bob White & Michael Sklarz, 2008. "ACross-Sectional Analysis of CapRates by MSA," Journal of Real Estate Research, American Real Estate Society, vol. 30(3), pages 249-292.
    23. Stefano Colonnello & Roberto Marfè & Qizhou Xiong, 2021. "Housing Yields," Working Papers 2021:21, Department of Economics, University of Venice "Ca' Foscari", revised 2021.
    24. Poh-Chin Lai & Si Chen & Chien-Tat Low & Ester Cerin & Robert Stimson & Pui Yun Paulina Wong, 2018. "Neighborhood Variation of Sustainable Urban Morphological Characteristics," IJERPH, MDPI, vol. 15(3), pages 1-13, March.
    25. Tom Emmerling & Crocker Liu & Yildiray Yildirim, 2017. "The Hybrid Nature of Real Estate Trusts," ERES eres2017_370, European Real Estate Society (ERES).
    26. Gregg Fisher & Eva Steiner & Sheridan Titman & Ashvin Viswanathan, 2022. "Location density, systematic risk, and cap rates: Evidence from REITs," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(2), pages 366-400, June.
    27. Frank J. Fabozzi & Iason Kynigakis & Ekaterini Panopoulou & Radu S. Tunaru, 2020. "Detecting Bubbles in the US and UK Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 469-513, May.
    28. Haroon Mumtaz & Roman Sustek, 2023. "Global house prices since 1950," Discussion Papers 2307, Centre for Macroeconomics (CFM).
    29. Xudong An & Yongheng Deng & Joseph Nichols & Anthony Sanders, 2015. "What is Subordination About? Credit Risk and Subordination Levels in Commercial Mortgage-backed Securities (CMBS)," The Journal of Real Estate Finance and Economics, Springer, vol. 51(2), pages 231-253, August.
    30. Chi-Young Choi & Alexander Chudik & Aaron Smallwood, 2024. "Time-varying Persistence of House Price Growth: The Role of Expectations and Credit Supply," Globalization Institute Working Papers 426, Federal Reserve Bank of Dallas.
    31. Kraft, Holger & Munk, Claus & Weiss, Farina, 2017. "Predictors and portfolios over the life cycle: Skill vs. luck," SAFE Working Paper Series 139, Leibniz Institute for Financial Research SAFE, revised 2017.
    32. Jędrzej Białkowski & Sheridan Titman & Garry Twite, 2023. "The determinants of office cap rates: The international evidence," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(3), pages 539-572, May.
    33. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    34. Alexander N. Bogin & LaRhonda Ealey & Kirsten Landeryou & Scott Smith & Andrew Tsai, 2023. "Geographic Disaggregation of House Price Stress Paths: Implications for Single-Family Credit Risk Measurement," FHFA Staff Working Papers 23-02, Federal Housing Finance Agency.
    35. Engsted, Tom & Pedersen, Thomas Q., 2014. "Housing market volatility in the OECD area: Evidence from VAR based return decompositions," Journal of Macroeconomics, Elsevier, vol. 42(C), pages 91-103.
    36. Christian Rehring, 2012. "Real Estate in a Mixed‐Asset Portfolio: The Role of the Investment Horizon," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 40(1), pages 65-95, March.
    37. Lucas Hafemann, 2021. "Prudential Policies in the Eurozone: A Propensity Score Matching Approach," MAGKS Papers on Economics 202109, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    38. Gupta, Arpit & Van Nieuwerburgh, Stijn & Kontokosta, Constantine, 2022. "Take the Q train: Value capture of public infrastructure projects," Journal of Urban Economics, Elsevier, vol. 129(C).
    39. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    40. Eduard Hromada & Tomáš Krulický, 2021. "Investing in Real Estate in the Czech Republic and Analyzing the Dependence of Profitability and Technical and Socio-Economic Factors," Sustainability, MDPI, vol. 13(18), pages 1-12, September.
    41. Helmut Herwartz & Fang Xu, 2020. "Low Mortgage Rates and Securitization: A Distinct Perspective on the US Housing Boom," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 164-190, January.
    42. Plogmann, Jana & Mußhoff, Oliver & Odening, Martin & Ritter, Matthias, 2020. "What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 69(1).
    43. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    44. Hiebert, Paul & Sydow, Matthias, 2009. "What drives returns to euro area housing? Evidence from a dynamic dividend-discount model," Working Paper Series 1019, European Central Bank.
    45. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
    46. Daniel Melser & Adrian D. Lee, 2014. "Estimating the Excess Returns to Housing at a Disaggregated Level: An Application to Sydney 2003–2011," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(3), pages 756-790, September.
    47. Liang Peng & Thomas G. Thibodeau, 2020. "Interest Rates and Investment: Evidence from Commercial Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 554-586, May.
    48. Galina An & Charles Becker & Enoch Cheng, 2021. "Bubbling Away: Forecasting Real Estate Prices, Rents, and Bubbles in a Transition Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 63(2), pages 263-317, June.
    49. Christian Rehring & Steffen Sebastian, 2010. "Dynamics Of Commercial Real Estate Asset Markets, Return Volatility, And The Investment Horizon," ERES eres2010_134, European Real Estate Society (ERES).
    50. Levon Goukasian & Mehdi Majbouri, 2010. "The Reaction of Real Estate–Related Industries to the Monetary Policy Actions," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 38(2), pages 355-398, June.
    51. Jianhua Gang & Liang Peng & Thomas G. Thibodeau, 2020. "Risk and Returns of Income Producing Properties: Core versus Noncore," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(2), pages 476-503, June.
    52. James D. Shilling & C.F. Sirmans & Barrett A. Slade, 2017. "Spatial Correlation in Expected Returns in Commercial Real Estate Markets and the Role of Core Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 54(3), pages 297-337, April.
    53. Jędrzej Białkowski & Sheridan Titman & Garry Twite, 2023. "The Determinants of Office Cap Rates: The International Evidence," Working Papers in Economics 23/01, University of Canterbury, Department of Economics and Finance.
    54. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2019. "Earnings yield and predictability in the dry bulk shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 140-159.
    55. Boudry, Walter I. & Kallberg, Jarl G. & Liu, Crocker H., 2013. "Investment opportunities and share repurchases," Journal of Corporate Finance, Elsevier, vol. 23(C), pages 23-38.

  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. 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.

    Cited by:

    1. Jim Clayton & David Ling & Andy Naranjo, 2009. "Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment," The Journal of Real Estate Finance and Economics, Springer, vol. 38(1), pages 5-37, January.
    2. Yuming Li & Jing Yang, 2018. "House Price Dynamics and Excess Risk," International Real Estate Review, Global Social Science Institute, vol. 21(2), pages 251-274.
    3. Zifeng Feng, 2022. "How Does Local Economy Affect Commercial Property Performance?," The Journal of Real Estate Finance and Economics, Springer, vol. 65(3), pages 361-383, October.
    4. Leung, Charles Ka Yui & Zhang, Jun, 2011. "“Fire Sales” in housing market: is the house-searching process similar to a theme park visit?," MPRA Paper 29127, University Library of Munich, Germany.
    5. Teulings, Coen & Lange, Rutger-Jan, 2021. "The option value of vacant land: Don't build when demand for housing is booming," CEPR Discussion Papers 16023, C.E.P.R. Discussion Papers.
    6. Tom Emmerling & Crocker Liu & Yildiray Yildirim, 2017. "The Hybrid Nature of Real Estate Trusts," ERES eres2017_370, European Real Estate Society (ERES).
    7. William G. Hardin & Xiaoquan Jiang & Zhonghua Wu, 2017. "Inflation Illusion, Expertise and Commercial Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 55(3), pages 345-369, October.
    8. Stephen Lee & Giacomo Morri, 2015. "Real estate fund active management," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 33(6), pages 494-516, September.
    9. Kevin C.H. Chiang & Xiaguan Jiang & Ming‐Long Lee, 2010. "REIT idiosyncratic risk," Journal of Property Research, Taylor & Francis Journals, vol. 26(4), pages 349-366, February.
    10. Daniel Melser & Adrian D. Lee, 2014. "Estimating the Excess Returns to Housing at a Disaggregated Level: An Application to Sydney 2003–2011," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(3), pages 756-790, September.
    11. Alexander Schätz & Steffen Sebastian, 2009. "The links between property and the economy -- evidence from the British and German markets," Journal of Property Research, Taylor & Francis Journals, vol. 26(2), pages 171-191, September.
    12. Christian Rehring & Steffen Sebastian, 2010. "Dynamics Of Commercial Real Estate Asset Markets, Return Volatility, And The Investment Horizon," ERES eres2010_134, European Real Estate Society (ERES).
    13. Charles Ka Yui Leung & Jun Zhang, 2011. ""Fire Sales" in Housing Market: Is the House- Search Process Similar to a Theme Park Visit?," International Real Estate Review, Global Social Science Institute, vol. 14(3), pages 311-329.
    14. Abdulmalik Fatimah Binta & Udoekanem Namnso Bassey, 2022. "Commercial Real Estate Rental Variation in Ilorin, Nigeria," Baltic Journal of Real Estate Economics and Construction Management, Sciendo, vol. 10(1), pages 140-155, January.
    15. Jianhua Gang & Liang Peng & Thomas G. Thibodeau, 2020. "Risk and Returns of Income Producing Properties: Core versus Noncore," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(2), pages 476-503, June.
    16. Alexey Akimov & Simon Stevenson & Maxim Zagonov, 2015. "Public Real Estate and the Term Structure of Interest Rates: A Cross-Country Study," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 503-540, November.

  9. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.

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    1. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
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    12. 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.
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    49. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    50. 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.
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    55. Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024. "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 3-25, June.
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    61. Tang, Zhenpeng & Lin, Qiaofeng & Cai, Yi & Chen, Kaijie & Liu, Dinggao, 2024. "Harnessing the power of real-time forum opinion: Unveiling its impact on stock market dynamics using intraday high-frequency data in China," International Review of Financial Analysis, Elsevier, vol. 93(C).
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    248. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    249. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    250. Schlag, Christian & Zeng, Kailin, 2019. "Horizontal industry relationships and return predictability," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 310-330.
    251. Robert N. Killins & Haiwei Chen, 2022. "The impact of the yield curve on the equity returns of insurance companies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1134-1153, January.
    252. Gelman, Sergey & Burhop, Carsten, 2008. "Taxation, regulation and the information efficiency of the Berlin stock exchange, 1892–1913," European Review of Economic History, Cambridge University Press, vol. 12(1), pages 39-66, April.
    253. Hirshleifer, David & Hsu, Po-Hsuan & Li, Dongmei, 2013. "Innovative efficiency and stock returns," Journal of Financial Economics, Elsevier, vol. 107(3), pages 632-654.
    254. Ólan Henry & Semih Kerestecioglu & Sam Pybis, 2024. "Can financial uncertainty forecast aggregate stock market returns?," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 33(2), pages 91-111, May.
    255. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    256. Chava, Sudheer & Hsu, Alex & Zeng, Linghang, 2020. "Does history repeat itself? Business cycle and industry returns," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 201-218.
    257. Nuno Silva, 2015. "Industry based equity premium forecasts," GEMF Working Papers 2015-19, GEMF, Faculty of Economics, University of Coimbra.
    258. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.
    259. Roger K. Loh, 2010. "Investor Inattention and the Underreaction to Stock Recommendations," Financial Management, Financial Management Association International, vol. 39(3), pages 1223-1252, September.
    260. Huang, Yisu & Ma, Feng & Bouri, Elie & Huang, Dengshi, 2023. "A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns," International Review of Financial Analysis, Elsevier, vol. 87(C).
    261. Xiao, Jihong & Jiang, Jiajie & Zhang, Yaojie, 2024. "Policy uncertainty, investor sentiment, and good and bad volatilities in the stock market: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
    262. Kailin Zeng & Ebenezer Fiifi Emire Atta Mills, 2023. "Can economic links explain lead–lag relations across firms?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1338-1363, April.
    263. Conlon, Thomas & Cotter, John & Gençay, Ramazan, 2018. "Long-run wavelet-based correlation for financial time series," European Journal of Operational Research, Elsevier, vol. 271(2), pages 676-696.
    264. Tolikas, Konstantinos & Topaloglou, Nikolas, 2017. "Is default risk priced equally fast in the credit default swap and the stock markets? AN empirical investigation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 39-57.
    265. Kenneth Högholm & Johan Knif & Gregory Koutmos & Seppo Pynnönen, 2021. "Financial crises and the asymmetric relation between returns on banks, risk factors, and other industry portfolio returns," The Financial Review, Eastern Finance Association, vol. 56(1), pages 179-198, February.
    266. Yanying Zhang & Yiuman Tse & Gaiyan Zhang, 2022. "Return predictability between industries and the stock market in China," Pacific Economic Review, Wiley Blackwell, vol. 27(2), pages 194-220, May.
    267. Lambertides, Neophytos & Savva, Christos S. & Tsouknidis, Dimitris A., 2017. "The effects of oil price shocks on U.S. stock order flow imbalances and stock returns," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 137-146.
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    270. Gregor Dorfleitner & Felix Rößle, 2018. "The financial performance of the health care industry: a global, regional and industry specific empirical investigation," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(4), pages 585-594, May.
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  11. 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.

    Cited by:

    1. David Ling & Gianluca Marcato & Pat McAllister, 2009. "Dynamics of Asset Prices and Transaction Activity in Illiquid Markets: the Case of Private Commercial Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 39(3), pages 359-383, October.
    2. Prashant Das & Patrick Smith & Paul Gallimore, 2018. "Pricing Extreme Attributes in Commercial Real Estate: the Case of Hotel Transactions," The Journal of Real Estate Finance and Economics, Springer, vol. 57(2), pages 264-296, August.
    3. Jack Corgel & Crocker Liu & Robert White, 2015. "Determinants of Hotel Property Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 51(3), pages 415-439, October.
    4. 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.
    5. 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.
    6. Frank J. Fabozzi & Robert J. Shiller & Radu S. Tunaru, 2012. "A Pricing Framework for Real Estate Derivatives," European Financial Management, European Financial Management Association, vol. 18(5), pages 762-789, November.
    7. Frank Fabozzi & Robert Shiller & Radu Tunaru, 2009. "Property Derivatives for Managing European Real-Estate Risk," Yale School of Management Working Papers amz2652, Yale School of Management, revised 01 Sep 2009.
    8. Bart Hobijn & John Krainer & David Lang, 2011. "Cap rates and commercial property prices," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue sep19.
    9. Füss, Roland & Ruf, Daniel, 2021. "Bank systemic risk exposure and office market interconnectedness," Journal of Banking & Finance, Elsevier, vol. 133(C).
    10. Jeffrey Fisher & David C. Ling & Andy Naranjo, 2009. "Institutional Capital Flows and Return Dynamics in Private Commercial Real Estate Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(1), pages 85-116, March.
    11. Christian Rehring, 2012. "Real Estate in a Mixed‐Asset Portfolio: The Role of the Investment Horizon," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 40(1), pages 65-95, March.
    12. Frank J. Fabozzi & Robert J. Shiller & Radu S. Tunaru, 2010. "Property Derivatives for Managing European Real†Estate Risk," European Financial Management, European Financial Management Association, vol. 16(1), pages 8-26, January.
    13. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    14. David C. Ling & Andy Naranjo & Benjamin Scheick, 2014. "Investor Sentiment, Limits to Arbitrage and Private Market Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(3), pages 531-577, September.
    15. Daniele Bianchi & Massimo Guidolin, 2014. "Can Linear Predictability Models Time Bull and Bear Real Estate Markets? Out-of-Sample Evidence from REIT Portfolios," The Journal of Real Estate Finance and Economics, Springer, vol. 49(1), pages 116-164, July.
    16. Ferentinos, Konstantinos & Gibberd, Alex & Guin, Benjamin, 2023. "Stranded houses? The price effect of a minimum energy efficiency standard," Energy Economics, Elsevier, vol. 120(C).
    17. David C. Ling & Andy Naranjo, 2015. "Returns and Information Transmission Dynamics in Public and Private Real Estate Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(1), pages 163-208, March.

  12. 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.
  13. Valkanov, Rossen, 2005. "Functional Central Limit Theorem approximations and the distribution of the Dickey-Fuller test with strongly heteroskedastic data," Economics Letters, Elsevier, vol. 86(3), pages 427-433, March.

    Cited by:

    1. Su, Jen-Je & Cheung, Adrian (Wai-Kong) & Roca, Eduardo, 2014. "Does Purchasing Power Parity hold? New evidence from wild-bootstrapped nonlinear unit root tests in the presence of heteroskedasticity," Economic Modelling, Elsevier, vol. 36(C), pages 161-171.
    2. Nikolay Gospodinov & Ye Tao, 2009. "Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors," Working Papers 09001, Concordia University, Department of Economics.
    3. Jürgen Wolters & Uwe Hassler, 2006. "Unit root testing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 43-58, March.

  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. Walter Torous & Rossen Valkanov & Shu Yan, 2004. "On Predicting Stock Returns with Nearly Integrated Explanatory Variables," The Journal of Business, University of Chicago Press, vol. 77(4), pages 937-966, October.

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    1. Martin Lettau & Stijn Van Nieuwerburgh, 2006. "Reconciling the Return Predictability Evidence," 2006 Meeting Papers 29, Society for Economic Dynamics.
    2. Fallahi, Firouz & Voia, Marcel-Cristian, 2015. "Convergence and persistence in per capita energy use among OECD countries: Revisited using confidence intervals," Energy Economics, Elsevier, vol. 52(PA), pages 246-253.
    3. Brunnermeier, Markus K. & Julliard, Christian, 2006. "Money illusion and housing frenzies," LSE Research Online Documents on Economics 4806, London School of Economics and Political Science, LSE Library.
    4. Andreou, Elena & Kasparis, Ioannis & Phillips, Peter C. B., 2013. "Nonparametric Predictive Regression," CEPR Discussion Papers 9570, C.E.P.R. Discussion Papers.
    5. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print hal-01386006, HAL.
    6. Hualde, Javier, 2014. "Estimation of long-run parameters in unbalanced cointegration," Journal of Econometrics, Elsevier, vol. 178(2), pages 761-778.
    7. De Villeris, David & Apopo, Natalya & Phiri, Andrew, 2018. "Unobserved structural shifts and asymmetries in the random walk model for stock returns in African frontier markets," MPRA Paper 87963, University Library of Munich, Germany.
    8. 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.
    9. Cai, Zongwu & Li, Qi & Park, Joon Y., 2009. "Functional-coefficient models for nonstationary time series data," Journal of Econometrics, Elsevier, vol. 148(2), pages 101-113, February.
    10. Simionescu, Mihaela, 2022. "Stochastic convergence in per capita energy use in the EU-15 countries. The role of economic growth," Applied Energy, Elsevier, vol. 322(C).
    11. Fallahi, Firouz & Karimi, Mohammad & Voia, Marcel-Cristian, 2016. "Persistence in world energy consumption: Evidence from subsampling confidence intervals," Energy Economics, Elsevier, vol. 57(C), pages 175-183.
    12. Wayne E. Ferson & Sergei Sarkissian & Timothy Simin, 2006. "Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression," NBER Working Papers 12658, National Bureau of Economic Research, Inc.
    13. David E. Rapach & Matthew C. Ringgenberg & Guofu Zhou, 2016. "Short interest and aggregate stock returns," CEMA Working Papers 716, China Economics and Management Academy, Central University of Finance and Economics.
    14. Hjalmarsson, Erik, 2008. "Interpreting long-horizon estimates in predictive regressions," Finance Research Letters, Elsevier, vol. 5(2), pages 104-117, June.
    15. Fallahi, Firouz, 2017. "Stochastic convergence in per capita energy use in world," Energy Economics, Elsevier, vol. 65(C), pages 228-239.
    16. Laimutė Urbšienė & Andrius Bugajevas & Marekas Pipiras, 2016. "The Impact Of Investment Horizon On The Return And Risk Of Investments In Securities In Lithuania," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 7(2).
    17. Zongwu Cai & Haiqiang Chen & Xiaosai Liao, 2020. "A New Robust Inference for Predictive Quantile Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202002, University of Kansas, Department of Economics, revised Feb 2020.
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    20. Aroh Nkechi Nympha. Ph.D & Egolum, Priscilla Uchenna. Ph.D & Chukwuani Victoria Nnenna. Ph.D, 2021. "Dividend Policy Determinants of Firm Value: Empirical Evidence from Listed Non-Financial Companies in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 5(07), pages 612-634, July.
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    26. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
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    35. Catherine Georgiou, 2020. "The British Stock Market under the Structure of Market Capitalization Value: New Evidence on its Predictive Content," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 13(3), pages 56-69, December.
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    38. Chang-Jin Kim & Cheolbeom Park, 2012. "Disappearing Dividends: Implications for the Dividend-Price Ratio and Return Predictability," Discussion Paper Series 1205, Institute of Economic Research, Korea University.
    39. Campbell, John & Vuolteenaho, Tuomo, 2004. "Bad Beta, Good Beta," Scholarly Articles 3122489, Harvard University Department of Economics.
    40. Maynard, Alex & Shimotsu, Katsumi, 2009. "Covariance-Based Orthogonality Tests For Regressors With Unknown Persistence," Econometric Theory, Cambridge University Press, vol. 25(1), pages 63-116, February.
    41. John Y. Campbell & Motohiro Yogo, 2002. "Efficient Tests of Stock Return Predictability," Harvard Institute of Economic Research Working Papers 1972, Harvard - Institute of Economic Research.
    42. Tae-Hwy Lee & Eric Hillebrand & Marcelo Medeiros, 2014. "Bagging Constrained Equity Premium Predictors," Working Papers 201421, University of California at Riverside, Department of Economics, revised Feb 2013.
    43. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    44. Alex Maynard, 2006. "The forward premium anomaly: statistical artefact or economic puzzle? New evidence from robust tests," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1244-1281, November.
    45. Hong, Harrison & Torous, Walter & Valkanov, Rossen, 2007. "Do industries lead stock markets?," Journal of Financial Economics, Elsevier, vol. 83(2), pages 367-396, February.
    46. Charlotte S. Hansen & Bjorn E. Tuypens, 2004. "Long-Run Regressions: Theory and Application to US Asset Markets," Finance 0410018, University Library of Munich, Germany.
    47. Erik Hjalmarsson, 2006. "Inference in Long-Horizon Regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.).
    48. Maio, Paulo, 2016. "Cross-sectional return dispersion and the equity premium," Journal of Financial Markets, Elsevier, vol. 29(C), pages 87-109.
    49. John Y. Campbell & Christopher Polk & Tuomo Vuolteenaho, 2005. "Growth or Glamour? Fundamentals and Systematic Risk in Stock Returns," Harvard Institute of Economic Research Working Papers 2082, Harvard - Institute of Economic Research.
    50. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
    51. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    52. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 1-21, February.
    53. Coqueret, Guillaume & Deguest, Romain, 2024. "Unexpected opportunities in misspecified predictive regressions," European Journal of Operational Research, Elsevier, vol. 318(2), pages 686-700.
    54. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    55. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    56. Borja Larrain & Motohiro Yogo, 2005. "Does firm value move too much to be justified by subsequent changes in cash flow?," Working Papers 05-18, Federal Reserve Bank of Boston.
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    Cited by:

    1. Martin Lettau & Stijn Van Nieuwerburgh, 2006. "Reconciling the Return Predictability Evidence," 2006 Meeting Papers 29, Society for Economic Dynamics.
    2. Nelson C. Mark & Donggyu Sul, 2004. "The Use of Predictive Regressions at Alternative Horizons in Finance and Economics," Finance 0409032, University Library of Munich, Germany.
    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. Jank, Stephan, 2012. "Changes in the composition of publicly traded firms: Implications for the dividend-price ratio and return predictability," CFR Working Papers 12-08, University of Cologne, Centre for Financial Research (CFR).
    5. Lloyd, Simon & Marin, Emile, 2020. "Exchange rate risk and business cycles," Bank of England working papers 872, Bank of England.
    6. Richard K. Crump & Stefano Eusepi & Emanuel Moench, 2016. "The term structure of expectations and bond yields," Staff Reports 775, Federal Reserve Bank of New York.
    7. 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.
    8. Federico M Bandi & Valentina Corradi & Daniel Wilhelm, 2016. "Possibly Nonstationary Cross-Validation," CeMMAP working papers CWP11/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Hali J. Edison & Francis E. Warnock, 2006. "Cross-border Listings, Capital Controls, and Equity Flows To Emerging Markets," NBER Working Papers 12589, National Bureau of Economic Research, Inc.
    10. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    11. David McMillan & Alan Speight, 2006. "Non-linear long horizon returns predictability: evidence from six south-east Asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(2), pages 95-111, June.
    12. Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
    13. Ralph S.J. Koijen & Stijn Van Nieuwerburgh, 2011. "Predictability of Returns and Cash Flows," Annual Review of Financial Economics, Annual Reviews, vol. 3(1), pages 467-491, December.
    14. Theologos Dergiades & Panos K. Pouliasis, 2021. "Should Stock Returns Predictability be hooked on Long Horizon Regressions?," Discussion Paper Series 2021_03, Department of Economics, University of Macedonia, revised Feb 2021.
    15. Chang, C-L. & Ilomäki, J. & Laurila, H. & McAleer, M.J., 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Econometric Institute Research Papers EI2018-39, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Lettau, Martin & Ludvigson, Sydney, 2002. "Expected Returns and Expected Dividend Growth," CEPR Discussion Papers 3507, C.E.P.R. Discussion Papers.
    17. Wayne E. Ferson & Sergei Sarkissian & Timothy Simin, 2006. "Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression," NBER Working Papers 12658, National Bureau of Economic Research, Inc.
    18. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
    19. Hjalmarsson, Erik, 2008. "Interpreting long-horizon estimates in predictive regressions," Finance Research Letters, Elsevier, vol. 5(2), pages 104-117, June.
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    175. Ventosa-Santaulària, Daniel & Noriega, Antonio E., 2015. "Long-run monetary neutrality under stochastic and deterministic trends," Economic Modelling, Elsevier, vol. 47(C), pages 372-382.
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    180. Ming, Lei & Song, Wuqi & Dong, Minyi, 2023. "Revisiting time series momentum in China's commodity futures market: Evidence on sources of momentum profits," Economic Modelling, Elsevier, vol. 128(C).
    181. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
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Chapters

  1. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.

    Cited by:

    1. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High-Frequency Impact of Monetary Policy and Macroeconomic Surprises on US MSAs and Aggregate US Housing Returns and Volatility: A GJR-GARCH Approach," Working Papers 201817, University of Pretoria, Department of Economics.
    2. Pedersen, Thomas Quistgaard & Schütte, Erik Christian Montes, 2020. "Testing for explosive bubbles in the presence of autocorrelated innovations," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 207-225.
    3. Bouri, Elie & Gupta, Rangan & Wong, Wing-Keung & Zhu, Zhenzhen, 2018. "Is wine a good choice for investment?," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 171-183.
    4. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy & Wohar, Mark E., 2018. "Do house prices hedge inflation in the US? A quantile cointegration approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 15-26.
    5. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    6. Klick, Larissa & Schaffner, Sandra, 2019. "FDZ data description: Regional real estate price indices for Germany (RWI-GEO-REDX) - Version 2: 2008-02/2019," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 202066.
    7. Engsted, Tom & Pedersen, Thomas Q., 2015. "Predicting returns and rent growth in the housing market using the rent-price ratio: Evidence from the OECD countries," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 257-275.
    8. Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014. "Forecasting the U.S. Real House Price Index," DUTH Research Papers in Economics 10-2014, Democritus University of Thrace, Department of Economics.
    9. Floro, Danvee, 2019. "Testing the predictive ability of house price bubbles for macroeconomic performance: A meta-analytic approach," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 164-181.
    10. Peter Chinloy & William D. Larson, 2017. "The Daily Microstructure of the Housing Market," FHFA Staff Working Papers 17-01, Federal Housing Finance Agency.
    11. Guglielmo Maria Caporale & Ricardo M. Sousa, 2011. "Consumption, Wealth, Stock and Housing Returns: Evidence from Emerging Markets," NIPE Working Papers 32/2011, NIPE - Universidade do Minho.
    12. Kraft, Holger & Munk, Claus & Weiss, Farina, 2019. "Predictors and portfolios over the life cycle," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 1-27.
    13. Glaeser, Edward L. & Nathanson, Charles G., 2017. "An extrapolative model of house price dynamics," Journal of Financial Economics, Elsevier, vol. 126(1), pages 147-170.
    14. Engsted, Tom & Hviid, Simon J. & Pedersen, Thomas Q., 2016. "Explosive bubbles in house prices? Evidence from the OECD countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 14-25.
    15. Tim Bollerslev & Andrew J. Patton & Wenjing Wang, 2016. "Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1005-1025, September.
    16. Joshua Aizenman & Yothin Jinjarak, 2013. "Real Estate Valuation, Current Account and Credit Growth Patterns, Before and After the 2008-9 Crisis," NBER Working Papers 19190, National Bureau of Economic Research, Inc.
    17. Ellington, Michael & Fu, Xi & Zhu, Yunyi, 2023. "Real estate illiquidity and returns: A time-varying regional perspective," International Journal of Forecasting, Elsevier, vol. 39(1), pages 58-72.
    18. Tim A. Kroencke & Felix Schindler & Bertram I. Steininger, 2018. "The Anatomy of Public and Private Real Estate Return Premia," The Journal of Real Estate Finance and Economics, Springer, vol. 56(3), pages 500-523, April.
    19. Lake, A., 2020. "Behavioural Finance at Home: Testing Deviations of House Prices from their Fundamental Values," Cambridge Working Papers in Economics 20104, Faculty of Economics, University of Cambridge.
    20. Hardik A. Marfatia & Rangan Gupta & Esin Cakan, 2017. "The International REIT's Time-Varying Response to the U.S. Monetary Policy and Macroeconomic Surprises," Working Papers 201712, University of Pretoria, Department of Economics.
    21. 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.
    22. Tim Meyer, 2019. "On the Directional Accuracy of United States Housing Starts Forecasts: Evidence from Survey Data," The Journal of Real Estate Finance and Economics, Springer, vol. 58(3), pages 457-488, April.
    23. Ainur A. Akhmetzianov & Andrew Y. Sokolov, 2021. "Financial and Strategic Pricing Analysis in the Development Market Using an Econometric Model," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 12(1), pages 144-148, January.
    24. Omokolade Akinsomi & Goodness C. Aye & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2016. "Real estate returns predictability revisited: novel evidence from the US REITs market," Empirical Economics, Springer, vol. 51(3), pages 1165-1190, November.
    25. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    26. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," Post-Print hal-01996210, HAL.
    27. Mehmet Balcilar & Rangan Gupta & Ricardo M. Sousa & Mark E. Wohar, 2021. "What Can Fifty-Two Collateralizable Wealth Measures Tell Us About Future Housing Market Returns? Evidence from U.S. State-Level Data," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 81-107, January.
    28. 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.
    29. Pablo Kurlat & Johannes Stroebel, 2014. "Testing for Information Asymmetries in Real Estate Markets," NBER Working Papers 19875, National Bureau of Economic Research, Inc.
    30. 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.
    31. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    32. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    33. Engsted, Tom & Pedersen, Thomas Q., 2014. "Housing market volatility in the OECD area: Evidence from VAR based return decompositions," Journal of Macroeconomics, Elsevier, vol. 42(C), pages 91-103.
    34. Klick, Larissa & Schaffner, Sandra, 2019. "FDZ data description: Regional real estate price indices for Germany (RWI-GEO-REDX)," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 195945.
    35. Odilon Costa & Franz Fuerst & Spenser Robinson & Wesley Mendes-da-Silva, 2017. "Are Green Labels More Valuable in Emerging Real Estate Markets?," LARES lares_2017_paper_5, Latin American Real Estate Society (LARES).
    36. Wei, Yu & Cao, Yang, 2017. "Forecasting house prices using dynamic model averaging approach: Evidence from China," Economic Modelling, Elsevier, vol. 61(C), pages 147-155.
    37. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    38. Krzysztof Olszewski, 2012. "The impact of commercial real estate on the financial sector, its tracking by central banks and some recommendations for the macro-financial stability policy of central banks," NBP Working Papers 132, Narodowy Bank Polski.
    39. Hardik A. Marfatia & Rangan Gupta & Keagile Lesame, 2021. "Dynamic Impact of Unconventional Monetary Policy on International REITs," JRFM, MDPI, vol. 14(9), pages 1-19, September.
    40. Goodness C. Aye & Christina Christou & Rangan Gupta & Christis Hassapis, 2024. "High-Frequency Contagion between Aggregate and Regional Housing Markets of the United States with Financial Assets: Evidence from Multichannel Tests," The Journal of Real Estate Finance and Economics, Springer, vol. 69(2), pages 253-276, August.
    41. Dooruj Rambaccussing, 2021. "The price–rent ratio inequality in Scottish Cities: fluctuations in discount rates and expected rent growth," SN Business & Economics, Springer, vol. 1(9), pages 1-15, September.
    42. Elie Bouri & Rangan Gupta & Shixuan Wang, 2019. "Contagion between Stock and Real Estate Markets: International Evidence from a Local Gaussian Correlation Approach," Working Papers 201917, University of Pretoria, Department of Economics.
    43. George Milunovich, 2020. "Forecasting Australia's real house price index: A comparison of time series and machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1098-1118, November.
    44. Diego Ardila & Dorsa Sanadgol & Peter Cauwels & Didier Sornette, 2017. "Identification and critical time forecasting of real estate bubbles in the USA," Quantitative Finance, Taylor & Francis Journals, vol. 17(4), pages 613-631, April.
    45. Kyriakou, Maria I. & Babalos, Vassilios & Kiohos, Apostolos & Koulakiotis, Athanasios, 2020. "Feedback trading strategies and long-term volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 181-189.
    46. Alessia Bruzzo & Marco Mazzoli, 2018. "An Empirical Investigation on the European Housing Market Prices," Review of Economics & Finance, Better Advances Press, Canada, vol. 12, pages 29-42, May.
    47. Nuri Hacıevliyagil & Krzysztof Drachal & Ibrahim Halil Eksi, 2022. "Predicting House Prices Using DMA Method: Evidence from Turkey," Economies, MDPI, vol. 10(3), pages 1-27, March.
    48. Liang Jiang & Peter C.B. Phillips & Jun Yu, 2014. "A New Hedonic Regression for Real Estate Prices Applied to the Singapore Residential Market," Cowles Foundation Discussion Papers 1969, Cowles Foundation for Research in Economics, Yale University.
    49. Eduardo Fernandes Cazassa & Odilon Costa, 2017. "Real Estate Indices: the good and the bad," LARES lares_2017_paper_65, Latin American Real Estate Society (LARES).
    50. Davis, Morris A. & Van Nieuwerburgh, Stijn, 2015. "Housing, Finance, and the Macroeconomy," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 753-811, Elsevier.
    51. Thiel, Patrick, 2024. "FDZ data description: Regional real estate price indices for Germany (RWI-GEO-REDX) - Version 13: 2008-11/2023," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 301663.
    52. Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016. "A New Index of Housing Sentiment," CREATES Research Papers 2016-32, Department of Economics and Business Economics, Aarhus University.
    53. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High Frequency Impact Of Monetary Policy And Macroeconomic Surprises On Us Msas, Aggregate Us Housing Returns And Asymmetric Volatility," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 204-229, December.
    54. Peter Chinloy & Cheng Jiang & Kose John, 2022. "Spreads and Volatility in House Returns," JRFM, MDPI, vol. 15(8), pages 1-16, August.
    55. Alisa Yusupova & Nicos G. Pavlidis & Efthymios G. Pavlidis, 2019. "Adaptive Dynamic Model Averaging with an Application to House Price Forecasting," Papers 1912.04661, arXiv.org.
    56. Schaffner, Sandra & Thiel, Patrick, 2024. "FDZ data description: Regional real estate price indices for Germany (RWI-GEO-REDX) - Version 12: 2008-11/2023," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 296882.
    57. Radosław Pietrzyk & Paweł Rokita, 2015. "Stochastic goals in financial planning for a two-person household," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(1), pages 111-136, May.

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