False (and Missed) Discoveries in Financial Economics
Campbell R. Harvey and
Journal of Finance, 2020, vol. 75, issue 5, 2503-2553
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.
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jfinan:v:75:y:2020:i:5:p:2503-2553
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