Investor Learning and Mutual Fund Flows
Jennifer C. Huang
University of Texas at Austin - Department of Finance
Kelsey D. Wei
University of Texas at Dallas
University of South Carolina; Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF)
January 15, 2012
AFA 2012 Chicago Meetings Paper
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.
Number of Pages in PDF File: 38
Keywords: Bayesian learning, mutual fund flows, volatility, flow-performance relationship
JEL Classification: G10, G11, G20, G23working papers series
Date posted: March 16, 2011 ; Last revised: January 31, 2012
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