Abstract

http://ssrn.com/abstract=391562
 
 

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Learning About Beta: Time-Varying Factor Loadings, Expected Returns, and the Conditional CAPM


Tobias Adrian


Federal Reserve Bank of New York

Francesco A. Franzoni


University of Lugano; Swiss Finance Institute

October 8, 2008

Federal Reserve Bank of New York Staff Report No. 193

Abstract:     
We complement the conditional CAPM by introducing unobservable long-run changes in risk factor loadings. In this environment, investors rationally 'learn' the long-level of factor loadings from the observation of realized returns. As a direct consequence of this assumption, conditional betas are modeled using the Kalman filter. Because of its focus on low frequency variation in betas, our approach circumvents recent criticisms of the conditional CAPM. When tested on portfolios sorted by size and book-to-market, our learning-augmented conditional CAPM fails to be rejected.

Number of Pages in PDF File: 48

Keywords: Asset Pricing, Bayesian Learning, CAPM Anomalies

JEL Classification: G12, C11

working papers series


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Date posted: April 9, 2003 ; Last revised: October 14, 2008

Suggested Citation

Adrian, Tobias and Franzoni, Francesco A., Learning About Beta: Time-Varying Factor Loadings, Expected Returns, and the Conditional CAPM (October 8, 2008). Federal Reserve Bank of New York Staff Report No. 193. Available at SSRN: http://ssrn.com/abstract=391562 or http://dx.doi.org/10.2139/ssrn.391562

Contact Information

Tobias Adrian (Contact Author)
Federal Reserve Bank of New York ( email )
33 Liberty Street
New York, NY 10045
United States
HOME PAGE: http://nyfedeconomists.org/adrian/
Francesco A. Franzoni
University of Lugano ( email ) ( email )
University of Lugano
Via G. Buffi 13
Lugano, 6904
Switzerland
Swiss Finance Institute ( email ) ( email )
University of Lugano
Via G. Buffi 13
Lugano, 6904
Switzerland
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