Which variables provide independent information about the cross-section of future returns? Portfolio sorts and Fama-MacBeth regressions cannot easily answer this question when the number of candidate variables is large and when cross-terms might be important. We introduce a new method based on...

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...

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...

We provide data and code that successfully reproduces nearly all cross-sectional stock return predictors. Unlike most metastudies, we carefully examine the original papers to determine whether our predictability tests should produce t-stats above 1.96. For the 180 predictors that were clearly...

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Unlike most metastudies, we carefully examine the original papers to determine whether our predictability tests should produce t-stats above 1.96. For the 180 predictors that were clearly...

Mining 29,000 accounting ratios for t-statistics over 2.0 leads to cross-sectional predictability similar to the peer review process. For both methods, about 50% of predictability remains after the original sample periods. Data mining generates other features of peer review including the rise in...

To examine whether theory helps predict the cross-section of returns, we combine text analysis of publications with out-of-sample tests. Based on the original texts, only 18% of predictors are attributed to risk-based theory. 59% are attributed to mispricing, and 23% have uncertain origins....

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Our 319 characteristics draw from previous meta-studies, but we differ by comparing our t-stats to the original papers' results. For the 161 characteristics that were clearly significant in...