Publication Bias and the Cross-Section of Stock Returns

73 Pages Posted: 30 Jun 2016 Last revised: 9 May 2018

Andrew Y. Chen

Federal Reserve Board

Tom Zimmermann

QuantCo, Inc.; University of Cologne

Multiple version iconThere are 2 versions of this paper

Date Written: May 3, 2018

Abstract

We develop an estimator for publication bias and apply it to 156 hedge portfolios based on published cross-sectional return predictors. Publication bias adjusted returns are only 13% smaller than in-sample returns. The small bias comes from the dispersion in returns across predictors, which is too large to be accounted for by data-mined noise. Among predictors that can survive journal review, a low t-stat hurdle of 1.8 controls for multiple testing using statistics recommended by Harvey, Liu, and Zhu (2015). The estimated bias is too small to account for the deterioration in returns after publication, suggesting an important role for mispricing.

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 (May 3, 2018). Available at SSRN: https://ssrn.com/abstract=2802357 or http://dx.doi.org/10.2139/ssrn.2802357

Andrew Y. Chen (Contact Author)

Federal Reserve Board ( email )

20th and C Streets, NW
Washington, DC 20551
United States
202-973-6941 (Phone)

HOME PAGE: http://https://sites.google.com/site/chenandrewy/

Tom Zimmermann

QuantCo, Inc. ( email )

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

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