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

  • Adrian, Tobias
  • Franzoni, Francesco

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.

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Article provided by Elsevier in its journal Journal of Empirical Finance.

Volume (Year): 16 (2009)
Issue (Month): 4 (September)
Pages: 537-556

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Handle: RePEc:eee:empfin:v:16:y:2009:i:4:p:537-556
Contact details of provider: Web page: http://www.elsevier.com/locate/jempfin

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