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A Comprehensive Look at the Empirical Performance of Equity Premium Prediction

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Cited by:

  1. Martin Lettau & Stijn Van Nieuwerburgh, 2008. "Reconciling the Return Predictability Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1607-1652, July.
  2. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
  3. Jäckel, Christoph, 2013. "Model uncertainty and expected return proxies," MPRA Paper 51978, University Library of Munich, Germany.
  4. Fernandez, Pablo & Aguirreamalloa, Javier & Liechtenstein, Heinrich, 2009. "The equity premium puzzle: High required equity premium, undervaluation and self fulfilling prophecy," IESE Research Papers D/821, IESE Business School.
  5. Croce, M.M. & Nguyen, Thien T. & Raymond, S. & Schmid, L., 2019. "Government debt and the returns to innovation," Journal of Financial Economics, Elsevier, vol. 132(3), pages 205-225.
  6. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
  7. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
  8. Hashmat Khan & Santosh Upadhayaya, 2020. "Does business confidence matter for investment?," Empirical Economics, Springer, vol. 59(4), pages 1633-1665, October.
  9. Kam Fong Chan & John G. Powell & Jing Shi & Tom Smith, 2018. "Dividend persistence and dividend behaviour," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(1), pages 127-147, March.
  10. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
  11. 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.
  12. Gric, Zuzana & Bajzík, Josef & Badura, Ondřej, 2023. "Does sentiment affect stock returns? A meta-analysis across survey-based measures," International Review of Financial Analysis, Elsevier, vol. 89(C).
  13. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
  14. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
  15. Massacci, Daniele & Kapetanios, George, 2024. "Forecasting in factor augmented regressions under structural change," International Journal of Forecasting, Elsevier, vol. 40(1), pages 62-76.
  16. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
  17. Konstantinos Metaxoglou & Davide Pettenuzzo & Aaron Smith, 2019. "Option-Implied Equity Premium Predictions via Entropic Tilting," Journal of Financial Econometrics, Oxford University Press, vol. 17(4), pages 559-586.
  18. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric loss functions and the rationality of expected stock returns," International Journal of Forecasting, Elsevier, vol. 27(2), pages 413-437.
  19. Robin Greenwood & Samuel G. Hanson, 2011. "Issuer Quality and the Credit Cycle," NBER Working Papers 17197, National Bureau of Economic Research, Inc.
  20. Stefan Nagel & Zhengyang Xu, 2022. "Asset Pricing with Fading Memory," The Review of Financial Studies, Society for Financial Studies, vol. 35(5), pages 2190-2245.
  21. Li, Xiyang & Chen, Xiaoyue & Li, Bin & Singh, Tarlok & Shi, Kan, 2022. "Predictability of stock market returns: New evidence from developed and developing countries," Global Finance Journal, Elsevier, vol. 54(C).
  22. Christis Katsouris, 2023. "Unified Inference for Dynamic Quantile Predictive Regression," Papers 2309.14160, arXiv.org, revised Nov 2023.
  23. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
  24. Nengjiu Ju & Jianjun Miao, 2012. "Ambiguity, Learning, and Asset Returns," Econometrica, Econometric Society, vol. 80(2), pages 559-591, March.
  25. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
  26. Zhang, Junyu & Ruan, Xinfeng & Zhang, Jin E., 2023. "Do short-term market swings improve realized volatility forecasts?," Finance Research Letters, Elsevier, vol. 58(PD).
  27. Li, Jiahan & Tsiakas, Ilias, 2017. "Equity premium prediction: The role of economic and statistical constraints," Journal of Financial Markets, Elsevier, vol. 36(C), pages 56-75.
  28. Favilukis, Jack & Lin, Xiaoji, 2016. "Does wage rigidity make firms riskier? Evidence from long-horizon return predictability," Journal of Monetary Economics, Elsevier, vol. 78(C), pages 80-95.
  29. Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2018. "Dissecting the 2007–2009 Real Estate Market Bust: Systematic Pricing Correction or Just a Housing Fad?," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 34-62.
  30. Hillebrand, Eric & Lukas, Manuel & Wei, Wei, 2021. "Bagging weak predictors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 237-254.
  31. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
  32. repec:cte:idrepe:24859 is not listed on IDEAS
  33. Boriss Siliverstovs, 2017. "International stock return predictability: on the role of the United States in bad and good times," Applied Economics Letters, Taylor & Francis Journals, vol. 24(11), pages 771-773, June.
  34. Dong Lou & Christopher Polk, 2022. "Comomentum: Inferring Arbitrage Activity from Return Correlations," The Review of Financial Studies, Society for Financial Studies, vol. 35(7), pages 3272-3302.
  35. Michael Pinelis & David Ruppert, 2020. "Machine Learning Portfolio Allocation," Papers 2003.00656, arXiv.org, revised Nov 2021.
  36. Davide Pettenuzzo & Allan Timmermann, 2017. "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 183-201, April.
  37. de Oliveira Souza, Thiago, 2016. "The size premium and intertemporal risk," Discussion Papers on Economics 3/2016, University of Southern Denmark, Department of Economics.
  38. 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).
  39. Libo Yin & Qingyuan Yang & Zhi Su, 2017. "Predictability of structural co-movement in commodity prices: the role of technical indicators," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 795-812, May.
  40. Schrimpf, Andreas, 2010. "International stock return predictability under model uncertainty," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1256-1282, November.
  41. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
  42. Roel van Elk & Marc van der Steeg & Dinand Webbink, 2013. "The effects of a special program for multi-problem school dropouts on educational enrolment, employment and criminal behaviour; Evidence from a field experiment," CPB Discussion Paper 241.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
  43. Andrew Clare & James Seaton & Peter N. Smith & Stephen Thomas, 2019. "The Rehabilitation of Glidepath Investing," Discussion Papers 19/17, Department of Economics, University of York.
  44. Robin Greenwood & Samuel G. Hanson, 2013. "Issuer Quality and Corporate Bond Returns," The Review of Financial Studies, Society for Financial Studies, vol. 26(6), pages 1483-1525.
  45. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
  46. Avdoulas, Christos & Bekiros, Stelios & Boubaker, Sabri, 2016. "Detecting nonlinear dependencies in eurozone peripheral equity markets: A multistep filtering approach," Economic Modelling, Elsevier, vol. 58(C), pages 580-587.
  47. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
  48. Julien Pénasse & Luc Renneboog, 2022. "Speculative Trading and Bubbles: Evidence from the Art Market," Management Science, INFORMS, vol. 68(7), pages 4939-4963, July.
  49. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
  50. 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.
  51. 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).
  52. Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2016. "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(3), pages 273-291.
  53. Paul Söderlind, 2006. "C-CAPM Refinements and the Cross-Section of Returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(1), pages 49-73, April.
  54. Laborda, Ricardo & Laborda, Juan, 2017. "Can tree-structured classifiers add value to the investor?," Finance Research Letters, Elsevier, vol. 22(C), pages 211-226.
  55. François Gourio, 2013. "Credit Risk and Disaster Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(3), pages 1-34, July.
  56. Wang, Yubao & Huang, Xiaozhou & Huang, Zhendong, 2024. "Energy-related uncertainty and Chinese stock market returns," Finance Research Letters, Elsevier, vol. 62(PB).
  57. Tae‐Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting Under Structural Breaks Using Improved Weighted Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1485-1501, December.
  58. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
  59. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
  60. Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.
  61. John Y. Campbell & Stefano Giglio & Christopher Polk, 2013. "Hard Times," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 3(1), pages 95-132.
    • John Y. Campbell & Stefano Giglio & Christopher Polk, 2010. "Hard Times," NBER Working Papers 16222, National Bureau of Economic Research, Inc.
    • Campbell, John Y. & Giglio, Stefano & Polk, Christopher, 2013. "Hard Times," Scholarly Articles 12172786, Harvard University Department of Economics.
  62. Assefa, Tibebe A. & Esqueda, Omar A. & Mollick, André Varella, 2017. "Stock returns and interest rates around the World: A panel data approach," Journal of Economics and Business, Elsevier, vol. 89(C), pages 20-35.
  63. Florian Huber & Gregor Kastner & Martin Feldkircher, 2019. "Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 621-640, August.
  64. Matthew Baron & Wei Xiong, 2017. "Credit Expansion and Neglected Crash Risk," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 713-764.
  65. Han, Liyan & Xu, Yang & Yin, Libo, 2017. "Does investor attention matter? The attention-return relation in gold futures market," Economics Discussion Papers 2017-37, Kiel Institute for the World Economy (IfW Kiel).
  66. Theologos Dergiades & Panos K. Pouliasis, 2023. "Should stock returns predictability be ‘hooked on’ long‐horizon regressions?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 718-732, January.
  67. Andrew Ang & Allan Timmermann, 2012. "Regime Changes and Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 313-337, October.
  68. Richard K. Crump & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Liberty Street Economics 20181004, Federal Reserve Bank of New York.
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  70. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
  71. Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.
  72. Odendahl, Florens & Rossi, Barbara & Sekhposyan, Tatevik, 2023. "Evaluating forecast performance with state dependence," Journal of Econometrics, Elsevier, vol. 237(2).
  73. Elyasiani, Elyas & Movaghari, Hadi, 2022. "Determinants of corporate cash holdings: An application of a robust variable selection technique," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 967-993.
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  77. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
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