Learning about beta: time-varying factor loadings, expected returns, and the conditional CAPM

Tobias Adrian () and Francesco Franzoni

No 193, Staff Reports from Federal Reserve Bank of New York

Abstract: We complement the conditional capital asset pricing model (CAPM) by introducing unobservable long-run changes in risk factor loadings. In this environment, investors rationally “learn” the long-run level of factor loading by observing 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 ratio, our learning-augmented conditional CAPM fails to be rejected. ; Original title: Learning about beta: a new look at CAPM tests.

Keywords: Capital assets pricing model; Investments (search for similar items in EconPapers)
Date: 2008
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Related works:
Working Paper: Learning about Beta: time-varying factor loadings, expected returns and the conditional CAPM (2005)
Working Paper: Learning about Beta: Time-Varying Factor Loadings, Expected Returns,and the Conditional CAPM
Journal Article: Learning about beta: Time-varying factor loadings, expected returns, and the conditional CAPM (2009)
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