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Does Academic Research Destroy Stock Return Predictability?
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DOI：10.1111/jofi.12365.png)
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Abstract
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We study the out-of-sample and post-publication return predictability of 97 variables shown to predict cross-sectional stock returns. Portfolio returns are 26% lower out-of-sample and 58% lower post-publication. The out-of-sample decline is an upper bound estimate of data mining effects. We estimate a 32% (58%-26%) lower return from publication-informed trading. Post-publication declines are greater for predictors with higher in-sample returns, and returns are higher for portfolios concentrated in stocks with high idiosyncratic risk and low liquidity. Predictor portfolios exhibit post-publication increases in correlations with other published-predictor portfolios. Our findings suggest that investors learn about mispricing from academic publications.
Keywords:
CROSS-SECTION
COSTLY ARBITRAGE
RISK
VOLATILITY
GROWTH
LIMITS
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Should Investors Follow the Prophets or the Bears? Evidence on the Use of Public Information by Analysts and Short Sellers.png)
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