Publication Bias and the Cross-Section of Stock Returns

68 Pages Posted: 30 Jun 2016 Last revised: 14 Oct 2019

See all articles by Andrew Y. Chen

Andrew Y. Chen

Board of Governors of the Federal Reserve System

Tom Zimmermann

University of Cologne; QuantCo, Inc.

Multiple version iconThere are 2 versions of this paper

Date Written: August 19, 2019


We develop an estimator for publication bias adjusted returns and apply it to 156 replications of published long-short portfolio returns. Bias-adjusted returns are only 12.3% smaller than 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 accounted for by data-mined noise. Our estimate is free of economic effects and small sample noise that cloud out-of-sample tests. The bias is much smaller than post-publication decay (p-value < 0.0001), suggesting mispricing is important. Our results offer a different perspective on recent papers that find most published predictors are likely false.

Keywords: Stock return anomalies, publication bias, data mining, mispricing, replication, p-hacking

JEL Classification: G10, G12

Suggested Citation

Chen, Andrew Y. and Zimmermann, Tom and Zimmermann, Tom, Publication Bias and the Cross-Section of Stock Returns (August 19, 2019). Available at SSRN: or

Andrew Y. Chen (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States
202-973-6941 (Phone)


Tom Zimmermann

QuantCo, Inc. ( email )

University of Cologne ( email )

Cologne, 50923

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