Journal article

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

  • Adrian,Tobias Federal Reserve Bank of New York, New York, United States
  • Franzoni, Francesco Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
Published in:
  • Journal of empirical finance. - Elsevier. - 2009, vol. 16, no. 4, p. 537-556
English 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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