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

David Blake, Tristan Caulfield, Christos Ioannidis, I P Tonks

Research output: Contribution to journalArticle

4 Citations (Scopus)
65 Downloads (Pure)

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 Econometrics
Volume183
Issue number2
Early online date10 Jun 2014
DOIs
Publication statusPublished - 1 Dec 2014

Fingerprint

Panel Method
Bootstrap Method
Managers
Benchmark
Evaluation
Non-normality
Equity
Charge
Mutual fund performance
Inference
Bootstrap method
Methodology

Keywords

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

Cite this

Improved inference in the evaluation of mutual fund performance using panel bootstrap methods. / Blake, David; Caulfield, Tristan; Ioannidis, Christos; Tonks, I P.

In: Journal of Econometrics, Vol. 183, No. 2, 01.12.2014, p. 202-210.

Research output: Contribution to journalArticle

Blake, David ; Caulfield, Tristan ; Ioannidis, Christos ; Tonks, I P. / Improved inference in the evaluation of mutual fund performance using panel bootstrap methods. In: Journal of Econometrics. 2014 ; Vol. 183, No. 2. pp. 202-210.
@article{6502661996694f01bdef8f0b2cd012ec,
title = "Improved inference in the evaluation of mutual fund performance using panel bootstrap methods",
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.",
keywords = "mutual funds, unit trusts, open-ended investment companies, performance measurement, factor benchmark models, panel methods, bootstrap methods",
author = "David Blake and Tristan Caulfield and Christos Ioannidis and Tonks, {I P}",
year = "2014",
month = "12",
day = "1",
doi = "10.1016/j.jeconom.2014.05.010",
language = "English",
volume = "183",
pages = "202--210",
journal = "Journal of Econometrics",
issn = "0304-4076",
publisher = "Elsevier",
number = "2",

}

TY - JOUR

T1 - Improved inference in the evaluation of mutual fund performance using panel bootstrap methods

AU - Blake, David

AU - Caulfield, Tristan

AU - Ioannidis, Christos

AU - Tonks, I P

PY - 2014/12/1

Y1 - 2014/12/1

N2 - 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.

AB - 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.

KW - mutual funds

KW - unit trusts

KW - open-ended investment companies

KW - performance measurement

KW - factor benchmark models

KW - panel methods

KW - bootstrap methods

U2 - 10.1016/j.jeconom.2014.05.010

DO - 10.1016/j.jeconom.2014.05.010

M3 - Article

VL - 183

SP - 202

EP - 210

JO - Journal of Econometrics

JF - Journal of Econometrics

SN - 0304-4076

IS - 2

ER -