False (and Missed) Discoveries in Financial Economics

Campbell R. Harvey and Yan Liu

Papers from arXiv.org

Abstract: Multiple testing plagues many important questions in finance such as fund and factor selection. We propose a new way to calibrate both Type I and Type II errors. Next, using a double-bootstrap method, we establish a t-statistic hurdle that is associated with a specific false discovery rate (e.g., 5%). We also establish a hurdle that is associated with a certain acceptable ratio of misses to false discoveries (Type II error scaled by Type I error), which effectively allows for differential costs of the two types of mistakes. Evaluating current methods, we find that they lack power to detect outperforming managers.

Date: 2020-06
New Economics Papers: this item is included in nep-rmg
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Citations: View citations in EconPapers (29)

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