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

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  • Tobias Adrian
  • Francesco Franzoni

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.

Suggested Citation

  • Tobias Adrian & Francesco Franzoni, 2008. "Learning about beta: time-varying factor loadings, expected returns, and the conditional CAPM," Staff Reports 193, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:193
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    More about this item

    Keywords

    Investments; capital asset pricing model;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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