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Market Efficiency and Return Predictability: A Dynamic Perspective

Author

Listed:
  • Anwen Yin
  • Yan Zhao
  • William Procasky

Abstract

We view the state of aggregate equity market efficiency as an unobserved, time-varying variable, and propose to use relative predictive gains as its proxy. Given the difficulties in meaningfully forecasting the equity premium in the presence of structural breaks and instabilities, we employ the novel methodology of robust forecast combination to obtain predictive gains, thus dynamically tracking the changing magnitude of market efficiency. The robust combinations alleviate the impact of over-penalizing an otherwise outperforming model for the occurrence of outliers owing to instability, thus providing a theoretical foundation for the benefits of combining forecasts in unstable environments. Our empirical results reveal an increasing degree of equity market efficiency, particularly since the 2000s. Attempting to explain the elusive nature of return predictability and rising market efficiency, we explore the impact of events such as the dot-com bubble, the Sarbanes-Oxley Act, and the advent of new information-sharing technology.

Suggested Citation

  • Anwen Yin & Yan Zhao & William Procasky, 2025. "Market Efficiency and Return Predictability: A Dynamic Perspective," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 17(10), pages 1-31, October.
    • Handle: RePEc:ibn:ijefaa:v:17:y:2025:i:10:p:31
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    References listed on IDEAS

    as
    1. Timmermann, Allan, 2008. "Reply to the discussion of Elusive Return Predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 29-30.
    2. 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.
    3. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
    4. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    5. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    6. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    7. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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