Journal of Financial and Quantitative Analysis Vol. 60 No. 3 2025

Mutual Funds’ Conditional Performance Free of Data Snooping Bias

Po-Hsuan Hsu¹; Ioannis Kyriakou²; Tren Ma³; Georgios Sermpinis⁴

¹ National Tsing Hua University · ² City, University of London · ³ University of Nottingham · ⁴ University of Glasgow

Abstract

We introduce a test to assess mutual funds’ “conditional” performance that is based on updated information and corrects data snooping bias. Our method, named the functional false discovery rate “plus” ( $ fFDR^+ $ ), incorporates fund characteristics in estimating fund performance free of data snooping bias. Simulations suggest that the $ fFDR^+ $ controls well the ratio of false discoveries and gains considerable power over prior methods that do not account for extra information. Portfolios of funds selected by the $ fFDR^+ $ outperform other tests not accounting for information updating, highlighting the importance of evaluating mutual funds from a conditional perspective.

DOI

10.1017/s0022109024000097

Volume

60

Issue

3

Pages

1373-1400

Language

en

Sources

bibtex:phds-export.bib crossref openalex

Cite

APA 7 MLA 9 Chicago (author–date) Harvard Elsevier Harvard (JFE, JBF…) The Accounting Review Academy of Management American Marketing Association INFORMS (Management Science) Copy citation Copied ✓