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

Tobias Adrian () and Francesco Franzoni

Journal of Empirical Finance, 2009, vol. 16, issue 4, pages 537-556

Abstract: We amend the conditional CAPM to allow for unobservable long-run changes in risk factor loadings. In this environment, investors rationally "learn" the long-run level of factor loadings from the observation of realized returns. As a consequence of this assumption, we model conditional betas 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 passes the specification tests.

Keywords: Beta; CAPM; Kalman; filter; Anomalies; Value; premium (search for similar items in EconPapers)
Date: 2009

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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 (2008)
Working Paper: Learning about Beta: Time-Varying Factor Loadings, Expected Returns,and the Conditional CAPM
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Persistent link: http://EconPapers.repec.org/RePEc:eee:empfin:v:16:y:2009:i:4:p:537-556

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