Improved inference in the evaluation of mutual fund performance using bootstrap methods

David Blake, Tristan Caulfield, Christos Ioannidis, Ian Tonks

Research output: Contribution to journalArticle

Abstract

Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the non-normality of individual mutual fund returns is accounted for by using panel bootstrap methods. We also augment the standard benchmark factors with fund-specific characteristics, such as fund size. Using a dataset of UK equity mutual fund returns, we find that fund size has a negative effect on the average fund manager’s benchmark-adjusted performance. Further, when we allow for time effects and the non-normality of fund returns, we find that there is no evidence that even the best performing fund managers can significantly out-perform the augmented benchmarks after fund management charges are taken into account.
Original languageEnglish
Pages (from-to)202-210
Number of pages9
JournalJournal of Applied Econometrics
Volume183
Issue number2
Early online date10 Jun 2014
DOIs
Publication statusPublished - 1 Dec 2014

Keywords

  • mutual funds
  • unit trusts
  • open-ended investment companies
  • performance measurement
  • factor benchmark models
  • panel methods
  • bootstrap methods

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