Working Paper
Publication Bias and the Cross-Section of Stock Returns
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 12% smaller than in-sample returns. The small bias comes from the dispersion of 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: Data mining; Mispricing; Publication bias; Stock return anomalies;
https://doi.org/10.17016/FEDS.2018.033
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File(s): File format is application/pdf https://www.federalreserve.gov/econres/feds/files/2018033pap.pdf
Authors
Bibliographic Information
Provider: Board of Governors of the Federal Reserve System (U.S.)
Part of Series: Finance and Economics Discussion Series
Publication Date: 2018-05-11
Number: 2018-033
Pages: 71 pages