Alpha and Performance Measurement: The Effects of Investor Disagreement and Heterogeneity




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    • Wayne Ferson is the Ivadelle and Theodore Johnson Chair in Banking and Finance, Marshall School of Business, University of Southern California, and Research Associate, National Bureau of Economic Research. Jerchern Lin is at the State University of New York (SUNY) at Buffalo. Portions of this work were initially prepared as a keynote address for the 16th Annual Pacific Basin Economics, Accounting and Management Conference and for the 2009 Northern Finance Association Meetings. We are grateful to two anonymous referees, George Aragon, Kerry Back, Stephen Brown (Acting Editor), Mendel Fygenson, Derek Horstmeyer, Juna Joenvaara, Raymond Kan, Min S. Kim, Mark Kritzman, Thierry Post, Sergei Sarkissian, and Rick Sias, and to participants in workshops at the University of Arizona, Claremont McKenna College, Erasmus University, the 2011 European Finance Association, Koc University, the 2011 McGill Asset Management Conference, the 2011 Nothern Finance Association meetings, the University of New South Wales, the University of Southern California, the University of Sydney, the University of Technology Sydney, the fall 2011 ICI/AIM Investment Center conference at the University of Texas, Tilburg University, the Spring 2011 CQA Conference, the 2011 Wharton Conference on Household and Portfolio Choice and Investment Decisions, and the University of Washington for suggestions and discussions.


The literature has not established that a positive alpha, as traditionally measured, means that an investor would want to buy a fund. When alpha is defined using the client's utility function, a positive alpha generally means the client would want to buy. When markets are incomplete, investors will disagree about the attractiveness of a fund. We provide bounds on the expected disagreement with a traditional alpha and study the cross-sectional relation of disagreement and investor heterogeneity with the flow response to past fund alphas. The effects are both economically and statistically significant.