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Asymptotic Inference for Performance Fees and the Predictability of Asset Returns
Authors:Michael W McCracken  Giorgio Valente
Institution:1. Research Division, Federal Reserve Bank of St. Louis, St. Louis, MO, 63166 (michael.w.mccracken@stls.frb.org);2. Department of Economics and Finance, College of Business, City University of Hong Kong, Kowloon, Hong Kong (g.valente@cityu.edu.hk)
Abstract:In this article, we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee—the amount an investor would be willing to pay to have access to an alternative predictive model used to make investment decisions. We establish that this fee can be asymptotically normal under modest assumptions. Monte Carlo evidence shows that our test can be accurately sized in reasonably large samples. We apply the proposed test to predictions of the U.S. equity premium.
Keywords:Economic value  Out-of-sample forecasting  Predictability  Utility-based comparisons
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