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Anomalies and the Expected Market Return

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  • XI DONG
  • YAN LI
  • DAVID E. RAPACH
  • GUOFU ZHOU

Abstract

We provide the first systematic evidence on the link between long‐short anomaly portfolio returns—a cornerstone of the cross‐sectional literature—and the time‐series predictability of the aggregate market excess return. Using 100 representative anomalies from the literature, we employ a variety of shrinkage techniques (including machine learning, forecast combination, and dimension reduction) to efficiently extract predictive signals in a high‐dimensional setting. We find that long‐short anomaly portfolio returns evince statistically and economically significant out‐of‐sample predictive ability for the market excess return. The predictive ability of anomaly portfolio returns appears to stem from asymmetric limits of arbitrage and overpricing correction persistence.

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  • Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
  • Handle: RePEc:bla:jfinan:v:77:y:2022:i:1:p:639-681
    DOI: 10.1111/jofi.13099
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