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Testing the economic value of asset return predictability

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Author Info

  • Michael W. McCracken
  • Giorgio Valente

Abstract

Economic value calculations are increasingly used to compare the predictive performance of competing models of asset returns. However, they lack a rigorous way to validate their evidence. This paper proposes a new methodology to test whether utility gains accruing to investors using competing predictive models are equal to zero. Monte Carlo evidence indicates that our testing procedure, that can account for estimation error in the asymptotic variance of the test statistic, provides accurately sized and powerful tests in empirically relevant sample sizes. We apply the test statistics proposed in the paper to revisit the predictability of the US equity premium by means of various predictors.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2012-049.

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Date of creation: 2012
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Handle: RePEc:fip:fedlwp:2012-049

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Keywords: Forecasting;

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References

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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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Cited by:
  1. Kole, H.J.W.G. & van Dijk, D.J.C., 2013. "How to Identify and Forecast Bull and Bear Markets?," ERIM Report Series Research in Management ERS-2013-016-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.

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