Performance Measurement with Uncertain Risk Loadings
Francesco A. Franzoni
University of Lugano; Swiss Finance Institute
Martin C. Schmalz
University of Michigan, Stephen M. Ross School of Business
January 28, 2016
Swiss Finance Institute Research Paper No. 13-41
Ross School of Business Paper No. 1194
The paper establishes a new empirical fact: mutual funds’ flow-performance sensitivity is a hump-shaped function of aggregate risk realizations. We then propose an explanation to rationalize this finding. We posit that rational investors use past performance to learn not only about manager skill but also about the fund risk loading. It follows that when the realization of aggregate risk is larger in absolute value, the signal about skill is noisier, and investors react less strongly to performance. Besides validating the theory as an explanation for the empirical fact, the data also provide support for some of the model's out-of-sample predictions.
Number of Pages in PDF File: 80
Keywords: Bayesian learning, parameter uncertainty, mutual funds, flow-performance, Kalman filter, beta
JEL Classification: G00, G20
Date posted: May 13, 2013 ; Last revised: February 3, 2016
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