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Mutual Fund Flows

Paper Session

Saturday, Jan. 5, 2019 10:15 AM - 12:15 PM

Hilton Atlanta, 212-213-214
Hosted By: American Finance Association
  • Chair: Marcin Kacperczyk, Imperial College London

What do Fund Flows Reveal about Asset Pricing Models and Investor Sophistication?

Narasimhan Jegadeesh
Emory University
Chandra Sekhar Mangipudi
Emory University


Recent papers use the relative strength of the relation between fund flows and alphas with respect to various multifactor models to draw inferences about the best asset pricing model and about investor sophistication. This paper analytically shows that such inferences are tenable only under a number of additional assumptions. The results of our simulations and empirical tests indicate that such comparisons are not reliable tests of asset pricing models. We also find that parsimonious factor models better predict future alphas than models with additional factors, and discuss its implications for evaluating investor sophistication.

How Fast Do Investors Learn? Asset Management Investors and Bayesian Learning

Chris Schwarz
University of California-Irvine
Zheng Sun
University of California-Irvine


We study how fast investors learn about manager skills by examining the speed at which their disagreement converges. Using a novel measure of disagreement, we find that hedge fund investors learn as fast as suggested by Bayes’ rule. However, we also find mutual fund investors learn much more slowly than Bayes’ rule. Mutual fund investors’ slow learning is not caused by investors potentially paying attention to different performance measures, institutional frictions such as loads, or lack of sophistication, but is likely due to a low payoff from learning. Our results suggest learning speed depends on the motivation of financial participants.

Marketing Mutual Funds

Nikolai Roussanov
University of Pennsylvania
Hongxun Ruan
Peking University
Yanhao Wei
University of Southern California


Marketing and distribution expenses constitute a large fraction of the cost of active management
in the mutual fund industry. We investigate their impact on the allocation of capital
to funds and on returns earned by mutual fund investors. We develop and estimate a structural
model of costly investor search and fund competition with learning about fund skill
and endogenous marketing expenditures. We find that marketing is nearly as important
as performance and fees for determining fund size. Restricting the amount that funds can
spend on marketing substantially improves investor welfare, as more capital is invested with
passive index funds and price competition decreases fees on actively managed funds. Average
alpha increases as active fund size is reduced, and the relationship between fund size and
fund manager skill net of fees is closer to that implied by a frictionless model. Decreasing
investor search costs would also imply a reduction in marketing expenses and management
fees as well as a shift towards passive investing.
Jonathan Berk
Stanford University
Savitar Sundaresan
Imperial College London
Ali Hortaçsu
University of Chicago
JEL Classifications
  • G1 - General Financial Markets