Investor Learning and Mutual Fund Flows

38 Pages Posted: 16 Mar 2011 Last revised: 31 Jan 2012

See all articles by Jennifer C. Huang

Jennifer C. Huang

University of Texas at Austin - Department of Finance

Kelsey D. Wei

University of Texas at Dallas

Hong Yan

Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF)

Date Written: January 15, 2012

Abstract

This paper investigates the implications of investor learning for the sensitivity of mutual fund flows to past performance. We illustrate theoretically that when some sophisticated investors learn from past fund performance to form their posterior expectations of managerial ability, the flow-performance sensitivity should be weaker for funds with more volatile past performance and longer track records. Moreover, the dampening effects of performance volatility and fund age on the flow-performance sensitivity should be stronger for funds attracting more sophisticated investors. We provide supporting evidence for this investor learning hypothesis using mutual fund flows and compare the relative level of sophistication among investors in load versus no-load funds, institutional versus retails funds, and star versus non-star funds.

Keywords: Bayesian learning, mutual fund flows, volatility, flow-performance relationship

JEL Classification: G10, G11, G20, G23

Suggested Citation

Huang, Jennifer Chunyan and Wei, Kelsey D. and Yan, Hong, Investor Learning and Mutual Fund Flows (January 15, 2012). AFA 2012 Chicago Meetings Paper, Available at SSRN: https://ssrn.com/abstract=972780 or http://dx.doi.org/10.2139/ssrn.972780

Jennifer Chunyan Huang (Contact Author)

University of Texas at Austin - Department of Finance ( email )

McCombs School of Business, B6600
Austin, TX 78712
United States
512-232-9375 (Phone)
512-471-5073 (Fax)

Kelsey D. Wei

University of Texas at Dallas ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States
9728835978 (Phone)

Hong Yan

Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF) ( email )

Shanghai Jiao Tong University
211 West Huaihai Road
Shanghai, 200030
China

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