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.
| Original language | English |
|---|---|
| Pages (from-to) | 639-681 |
| Number of pages | 43 |
| Journal | The Journal of Finance |
| Volume | 77 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2022 |
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