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Asymptotic Inference for Performance Fees and the Predictability of Asset Returns

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In this paper 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 that is 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 US equity premium.

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File URL: http://research.stlouisfed.org/wp/2012/2012-049.pdf
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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2012-049.

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Length: 36 pages
Date of creation: 2012
Date of revision: 01 Jul 2016
Handle: RePEc:fip:fedlwp:2012-049
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  1. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
  2. Allan Timmermann & Andrew Patton, 2004. "Properties of Optimal Forecasts under Asymmetric Loss and Nonlinearity," Working Papers wp04-05, Warwick Business School, Finance Group.
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