Luck versus Skill in Mutual Funds: Size and Power Pitfalls in Bootstrap Methods

33 Pages Posted: 8 Nov 2019

See all articles by Haitao Huang

Haitao Huang

J. Mack Robinson College of Business, Georgia State University

Lei Jiang

Tsinghua University

Xuan Leng

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE)

Liang Peng

Georgia State University

Date Written: October 25, 2019

Abstract

We question the applicability of existing bootstrap methods for mutual fund performance evaluation, where the number of funds is large relative to the sample size of each fund. Theoretically, we derive the asymptotic distribution of the bootstrap test statistics by using Edgeworth expansion to characterize the approximation error in estimating alpha. We demonstrate that the test size is severely distorted as a large fraction of funds has small sample sizes and that the test power depends on the existence of both negative and positive alphas. Empirically, we design a simulation study to support our theoretical findings.

Keywords: Bootstrap, Edgeworth expansion, Estimation error, Mutual fund, Test size and power

JEL Classification: G11, G23, C58

Suggested Citation

Huang, Haitao and Jiang, Lei and Leng, Xuan and Peng, Liang, Luck versus Skill in Mutual Funds: Size and Power Pitfalls in Bootstrap Methods (October 25, 2019). Available at SSRN: https://ssrn.com/abstract=3475264 or http://dx.doi.org/10.2139/ssrn.3475264

Haitao Huang

J. Mack Robinson College of Business, Georgia State University ( email )

35 Broad St
Atlanta, GA 30303
United States

Lei Jiang (Contact Author)

Tsinghua University ( email )

Beijing, 100084
China

Xuan Leng

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Liang Peng

Georgia State University

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