Does Academic Research Destroy Stock Return Predictability?
R. David McLean
University of Alberta - Department of Finance and Statistical Analysis
Boston College - Department of Finance
June 30, 2014
AFFI/EUROFIDAI, Paris December 2012 Finance Meetings Paper
We study the out-of-sample and post-publication return-predictability of 95 characteristics that published academic studies show to predict cross-sectional stock returns. We estimate an upper bound decline in predictability due to statistical bias of 25%, and a post-publication decline, which we attribute to both statistical bias and informed trading, of 56%. Our findings support the contention that investors learn about mispricing from publications. Post-publication declines are greater for predictors with larger in-sample returns, and returns are lower for predictors concentrated in stocks with low idiosyncratic risk and high liquidity. Post-publication, predictor portfolios exhibit increases in correlations with other portfolios that are based on published predictors.
Number of Pages in PDF File: 48
Keywords: anomalies, arbitrage, limits of arbitrage, short selling, predicting stock returns
JEL Classification: G11, G12, G00, G14, L3, C1working papers series
Date posted: October 4, 2012 ; Last revised: July 1, 2014
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