Reassessing False Discoveries in Mutual Fund Performance: Skill, Luck, or Lack of Power? A Reply

Laurent Barras, Olivier Scaillet and Russell Wermers ()
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Laurent Barras: McGill University - Desautels Faculty of Management

No 19-61, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Andrikogiannopoulou and Papakonstantinou (AP; 2019) conduct an inquiry into the bias of the False Discovery Rate (FDR) estimators of Barras, Scaillet, and Wermers (BSW; 2010). In this Reply, we replicate their results, then further explore the bias issue by (i) using different parameter values, and (ii) updating the sample period. Over the original period (1975-2006), we show how reasonable adjustments to the parameter choices made by BSW and AP results in a sizeable reduction in the bias relative to AP. Over the updated period (1975-2018), we further 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, in combination 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.

Keywords: False Discovery Rate; Multiple Testing; Mutual Fund Performance (search for similar items in EconPapers)
JEL-codes: C11 G12 G23 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2019-08
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1961

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