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Reassessing false discoveries in mutual fund performance: skill, luck, or lack of power? a reply

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Barras, Laurent
Wermers, Russ
Published in Journal of Finance. 2020, p. 48
Abstract Andrikogiannopoulou and Papakonstantinou (2019, AP) inquire into the bias of the False Discovery Rate (FDR) estimators of Barras, Scaillet, and Wermers (2010, BSW). In this Reply, we replicate their results, then explore the bias issue further by (i) using different parameter values and (ii) updating the sample period. Over the original period (1975 to 2006), we show that reasonable adjustments to the parameter choices made by BSW and AP result in a sizeable reduction in the bias relative to AP. Over the updated period (1975 to 2018), we show that the performance of the FDR improves dramatically across a large range of parameter values. Specifically, we find that the probability of misclassifying a fund with a true alpha of 2% per year is 32% (versus 65% in AP). Our results, together with those of AP, indicate that the use of the FDR in finance should be accompanied by a careful evaluation of the underlying data-generating process, especially when the sample size is small.
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BARRAS, Laurent, SCAILLET, Olivier, WERMERS, Russ. Reassessing false discoveries in mutual fund performance: skill, luck, or lack of power? a reply. In: Journal of Finance, 2020, p. 48. doi: 10.37214/jofweb.2 https://archive-ouverte.unige.ch/unige:132900

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Deposited on : 2020-03-24

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