Asymptotic Inference for Performance Fees and the Predictability of Asset Returns

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
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Author(s)

  • Michael W. McCracken
  • Giorgio Valente

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)426-437
Journal / PublicationJournal of Business and Economic Statistics
Volume36
Issue number3
Online published10 May 2017
Publication statusPublished - 2018

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.

Research Area(s)

  • Economic value, Out-of-sample forecasting, Predictability, Utility-based comparisons