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Asymptotic Inference for Performance Fees and the Predictability of Asset Returns

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Abstract

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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  • McCracken, Michael W. & Valente, Giorgio, 2012. "Asymptotic Inference for Performance Fees and the Predictability of Asset Returns," Working Papers 2012-049, Federal Reserve Bank of St. Louis, revised 01 Jul 2016.
  • Handle: RePEc:fip:fedlwp:2012-049
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    1. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
    2. Valentina Corradi & Norman R. Swanson, 2007. "Nonparametric Bootstrap Procedures For Predictive Inference Based On Recursive Estimation Schemes," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 67-109, February.
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    Cited by:

    1. Li, Jiahan & Tsiakas, Ilias, 2017. "Equity premium prediction: The role of economic and statistical constraints," Journal of Financial Markets, Elsevier, vol. 36(C), pages 56-75.
    2. repec:wly:japmet:v:32:y:2017:i:1:p:120-139 is not listed on IDEAS
    3. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    4. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.

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    Forecasting;

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