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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Business & Economic Statistics.
Volume (Year): 31 (2013)
Issue (Month): 1 (January)
Contact details of provider:
Web page: http://www.tandfonline.com/UBES20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- 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).
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.