Mutual Fund Families and Performance Evaluation

47 Pages Posted: 12 Mar 2011

See all articles by David P. Brown

David P. Brown

University of Wisconsin - Madison - Department of Finance, Investment and Banking

Youchang Wu

University of Oregon - Lundquist College of Business

Date Written: February 2011

Abstract

We develop a continuous-time Bayesian learning model to evaluate the composite skill of a mutual fund manager and a fund family. Our model estimates the composite skill of each fund as a function of its own performance and family performance. We show two competing effects of the family performance on the evaluation of a member fund: a positive common-skill effect and a negative common-noise effect. The overall effect increases with the correlation of unobservable skills, and decreases with the correlation of unobservable noise. This pattern is stronger in larger families. Consistent with our assumptions, we find empirically that funds within the same family show higher correlations of estimated alphas and of residual returns. We also find that the effect of family performance on flows to a member fund exhibits strong cross-sectional patterns that are consistent with our model predictions.

Keywords: Mutual funds, performance evaluation, Bayesian learning, mutual fund flow

JEL Classification: G11, G20

Suggested Citation

Brown, David P. and Wu, Youchang, Mutual Fund Families and Performance Evaluation (February 2011). AFA 2012 Chicago Meetings Paper, Available at SSRN: https://ssrn.com/abstract=1782123 or http://dx.doi.org/10.2139/ssrn.1782123

David P. Brown (Contact Author)

University of Wisconsin - Madison - Department of Finance, Investment and Banking ( email )

975 University Avenue
Madison, WI 53706
United States
608-265-5281 (Phone)
608-265-4195 (Fax)

Youchang Wu

University of Oregon - Lundquist College of Business ( email )

1280 University of Oregon
Eugene, OR 97403
United States

HOME PAGE: http://www.youchangwu.com

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
57
Abstract Views
863
Rank
659,215
PlumX Metrics