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Multifactor Efficiency and Bayesian Inference

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Author Info
K. J. Martijn Cremers (Yale School of Management)
Abstract

This article reinvestigates the performance of risk-based multifactor models. We generalize the Bayesian methodology of Shanken and Kandel, McCulloch, and Stambaugh from mean-variance to multifactor efficiency. Using informative priors, our flexible framework handles severe small-sample problems. We introduce a new inefficiency metric that measures the maximum correlation between the market portfolio and any multifactor-efficient portfolio. Finally, we present new empirical evidence that neither the two additional Fama-French factors nor the momentum factor move the market portfolio robustly closer to being multifactor efficient or robustly decrease pricing errors relative to the Capital Asset Pricing Model.

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File URL: http://www.journals.uchicago.edu/cgi-bin/resolve?JB790608
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Publisher Info
Article provided by University of Chicago Press in its journal Journal of Business.

Volume (Year): 79 (2006)
Issue (Month): 6 (November)
Pages: 2951-2998
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:ucp:jnlbus:v:79:y:2006:i:6:p:2951-2998

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This page was last updated on 2009-12-2.


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