Abstract
Harvey, Liu, and Zhu (2016) “argue that most claimed research findings in financial economics are likely false.” Surprisingly, their false discovery rate (FDR) estimates suggest most are true. I revisit their results by developing non- and semi-parametric FDR estimators that account for publication bias and empirical correlations. These estimators provide simple closed-form expressions and reliably produce an upper bound on the FDR in simulations that cluster-bootstrap from empirical predictor returns. Applying these estimators to the Chen-Zimmermann dataset of 205 predictors, I find that most claimed statistical findings in the cross-sectional predictability literature are likely true.
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