Publication Bias and the Cross-Section of Stock Returns

Author:

Chen Andrew Y1,Zimmermann Tom2

Affiliation:

1. Federal Reserve Board

2. University of Cologne

Abstract

Abstract We develop an estimator for publication bias-adjusted returns and apply it to 156 published long-short portfolios. Our adjustment uses only in-sample data and provides sharper inferences than out-of-sample tests. Bias-adjusted returns are only 12.3% smaller than in-sample returns with a standard error of 1.7 percentage points. The small bias comes from the dispersion of returns across predictors, which is too large to be explained by data-mined noise. The bias is much smaller than post-publication decay (p-value ¡.0001), suggesting mispricing is important. Our results offer a different perspective about recent papers that find most published predictors are likely false. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Publisher

Oxford University Press (OUP)

Subject

Economics and Econometrics,Finance

Reference43 articles.

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2. Identification of and correction for publication bias;Andrews;American Economic Review,2019

3. The cross-section of volatility and expected returns;Ang;Journal of Finance,2006

4. The control of the false discovery rate in multiple testing under dependency;Benjamini;Annals of Statistics,2001

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