Abstract

http://ssrn.com/abstract=2263944
 
 

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Performance Measurement with Uncertain Risk Loadings


Francesco A. Franzoni


University of Lugano; Swiss Finance Institute

Martin C. Schmalz


The Stephen M. Ross School of Business at the University of Michigan

September 3, 2014

Swiss Finance Institute Research Paper No. 13-41
Ross School of Business Paper No. 1194

Abstract:     
We develop a model in which rational investors allocate capital to projects with uncertain risk exposure. Investors learn the projects' quality from project cash flows, conditioning on the systematic risk-factor realization. We show that the signal-to-noise ratio is highest when risk-factor realizations are close to zero. As a result, investors redirect more resources across projects during “moderate” times than during times with more “extreme” risk-factor realizations. We measure the speed of capital reallocation between projects with the sensitivity of mutual fund flows to performance and find supporting evidence for the model's qualitative and quantitative predictions.

Number of Pages in PDF File: 53

Keywords: Bayesian learning, parameter uncertainty, mutual funds, flow-performance

JEL Classification: G00, G20

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Date posted: May 13, 2013 ; Last revised: September 4, 2014

Suggested Citation

Franzoni, Francesco A. and Schmalz, Martin C., Performance Measurement with Uncertain Risk Loadings (September 3, 2014). Swiss Finance Institute Research Paper No. 13-41; Ross School of Business Paper No. 1194. Available at SSRN: http://ssrn.com/abstract=2263944 or http://dx.doi.org/10.2139/ssrn.2263944

Contact Information

Francesco A. Franzoni
University of Lugano ( email ) ( email )
University of Lugano
Via G. Buffi 13
Lugano, 6904
Switzerland
Swiss Finance Institute ( email ) ( email )
University of Lugano
Via G. Buffi 13
Lugano, 6904
Switzerland
Martin C. Schmalz (Contact Author)
The Stephen M. Ross School of Business at the University of Michigan ( email )
701 Tappan St
R5456
Ann Arbor, MI 48109-1234
United States
7347630304 (Phone)
HOME PAGE: http://https://sites.google.com/site/martincschmalz/
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