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Does Academic Research Destroy Stock Return Predictability?

The Journal of finance (New York), 2016-02, Vol.71 (1), p.5-32 [Peer Reviewed Journal]

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Title:
Does Academic Research Destroy Stock Return Predictability?
Author: MCLEAN, R. DAVID ; PONTIFF, JEFFREY
Subjects: Arbitrage ; Financial portfolios ; Idiosyncratic risk ; Investors ; Price momentum ; Prices ; Statistical bias ; Statistical significance ; Stock prices ; Stock shares
Is Part Of: The Journal of finance (New York), 2016-02, Vol.71 (1), p.5-32
Description: 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.
Publisher: Blackwell Publishing Ltd
Language: English
Identifier: ISSN: 0022-1082
EISSN: 1540-6261
DOI: 10.1111/jofi.12365
Source: Alma/SFX Local Collection

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