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

Federal Reserve Bank of New York Staff Report No. 193

48 Pages Posted: 9 Apr 2003 Last revised: 14 Oct 2008

Tobias Adrian

International Monetary Fund

Francesco A. Franzoni

Università della Svizzera italiana (USI), Lugano; Swiss Finance Institute

Multiple version iconThere are 2 versions of this paper

Date Written: October 8, 2008

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.

Keywords: Asset Pricing, Bayesian Learning, CAPM Anomalies

JEL Classification: G12, C11

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: https://ssrn.com/abstract=391562 or http://dx.doi.org/10.2139/ssrn.391562

Tobias Adrian (Contact Author)

International Monetary Fund ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

HOME PAGE: http://www.tobiasadrian.com

Francesco A. Franzoni

Università della Svizzera italiana (USI), Lugano ( email )

Via G. Buffi 13
Lugano, 6904
Switzerland

Swiss Finance Institute

Switzerland

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