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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.