Publication Bias and the Cross-Section of Stock Returns

65 Pages Posted: 30 Jun 2016 Last revised: 2 Nov 2018

See all articles by Andrew Y. Chen

Andrew Y. Chen

Federal Reserve Board

Tom Zimmermann

QuantCo, Inc.; University of Cologne

Multiple version iconThere are 2 versions of this paper

Date Written: November 1, 2018


We develop an estimator for publication bias and apply it to 156 replications of published hedge portfolios. 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 uses only in-sample data and is free of economic effects that cloud out-of-sample tests. An alternative dataset of 77 hand-collected portfolios leads to a 9.9% adjustment. The bias is much smaller than post-publication decay (p-value < 0.0001), suggesting mispricing is important.

Keywords: Stock return anomalies, publication bias, data mining, mispricing

JEL Classification: G10, G12

Suggested Citation

Chen, Andrew Y. and Zimmermann, Tom, Publication Bias and the Cross-Section of Stock Returns (November 1, 2018). Available at SSRN: or

Andrew Y. Chen (Contact Author)

Federal Reserve Board ( email )

20th and C Streets, 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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