Evaluating alternative methods for testing asset pricing models with historical data

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Abstract

We follow the correct Jagannathan and Wang (2002) framework for comparing the estimates and specification tests of the classical Beta and Stochastic Discount Factor/Generalized Method of Moments (SDF/GMM) methods. We extend previous studies by considering not only single but also multifactor models, and by taking into account some of the prescriptions for improving empirical tests suggested by Lewellen, Nagel and Shanken (2010). Our results reveal that SDF/GMM first-stage estimators lead to lower pricing errors than OLS, while SDF/GMM second stage estimators display higher pricing errors than the classical Beta GLS method. While Jagannathan and Wang (2002), and Cochrane (2005) conclude that there are no differences when estimating and testing by the Beta and SDF/GMM methods for the CAPM, we show that their conclusion cannot be extensible for multifactor models. Moreover, the Beta methods (OLS and GLS) seem to dominate the SDF/GMM (first and second stages) procedure in terms of estimators' properties. These results are consistent across benchmark portfolios and sample periods.
Original languageEnglish
Pages (from-to)136–146
Number of pages11
JournalJournal of Empirical Finance
Volume18
Issue number1
DOIs
Publication statusPublished - Jan 2011

Bibliographical note

Funding Information:
The authors thank participants in the XV Foro de Finanzas at Universidad Islas Baleares, and especially Belén Nieto, Rosa Rodríguez and Miguel A. Martínez for helpful comments and suggestions, and seminar participants at Universidad del País Vasco. We are especially indebted to an anonymous referee for his thoughtful suggestions which greatly improved the paper. Martín Lozano acknowledges financial support from Consolidate Research Team 9/UPV-00038.321-15094/2001 and Gonzalo Rubio acknowledges financial support from Generalitat Valenciana grant PROMETEO/2008/106 , and Ministerio de Ciencia e Innovación grant MEC ECO2008-03058/ECON .

Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics

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