• Media type: E-Book
  • Title: Reassessing false discoveries in mutual fund performance: skill, luck, or lack of power? : a reply
  • Contributor: Barras, Laurent [VerfasserIn]; Scaillet, Olivier [VerfasserIn]; Wermers, Russ [VerfasserIn]
  • imprint: Geneva: Swiss Finance Institute, 2019
  • Published in: Swiss Finance Institute: Research paper series ; 2019,61
  • Issue: This version: October 24, 2019
  • Extent: 1 Online-Ressource (circa 37 Seiten); Illustrationen
  • Language: English
  • DOI: 10.2139/ssrn.3439231
  • Identifier:
  • Keywords: Graue Literatur
  • Origination:
  • Footnote:
  • Description: 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
  • Access State: Open Access