Testing Linear Factor Pricing Models With Large Cross Sections: A Distribution-Free Approach
AbstractIn this article, we develop a finite-sample distribution-free procedure to test the beta-pricing representation of linear factor pricing models. In sharp contrast to extant finite-sample tests, our framework allows for unknown forms of nonnormalities, heteroscedasticity, and time-varying covariances. The power of the proposed test procedure increases as the time series lengthens and/or the cross section becomes larger. So the criticism sometimes heard that nonparametric tests lack power does not apply here, since the number of test assets is chosen by the user. This also stands in contrast to the usual tests that lose power or may not even be computable if the number of test assets is too large. Supplementary materials for this article are available online.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Business & Economic Statistics.
Volume (Year): 31 (2013)
Issue (Month): 1 (January)
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- Pesaran, M. H. & Yamagata, T., 2012. "Testing CAPM with a Large Number of Assets (Updated 28th March 2012)," Cambridge Working Papers in Economics 1210, Faculty of Economics, University of Cambridge.
- Pesaran, M. Hashem & Yamagata, Takashi, 2012.
"Testing CAPM with a Large Number of Assets,"
IZA Discussion Papers
6469, Institute for the Study of Labor (IZA).
- Sermin Gungor & Richard Luger, 2013. "Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances," Working Papers 13-16, Bank of Canada.
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