Anomalies and the Expected Market Return
67 Pages Posted: 7 Apr 2020
Date Written: March 21, 2020
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. Economically, the predictive ability of anomaly portfolio returns appears to stem from asymmetric limits of arbitrage and overpricing dominance.
Keywords: Out-of-sample predictability, market excess return, long-short anomaly portfolio return, machine learning, asymmetric limits of arbitrage, overpricing dominance
JEL Classification: G11, G14
Suggested Citation: Suggested Citation