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Learning about Beta: Time-varying factor loadings, expected returns, and the Conditional CAPM

Author

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  • Francesco Franzoni

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • Tobias Adrian

Abstract

This paper explores the theoretical and empirical implications of time-varying and unobservable beta. Investors infer factor loadings from the history of returns via the Kalman filter. Due to learning, the history of beta matters. Even though the conditional CAPM holds, standard OLS tests can reject the model if the evolution of investor's expectations is not properly modelled. We use our methodology to explain returns on the twenty-five size and book-to-market sorted portfolios. Our learning version of the conditional CAPM produces pricing errors that are significantly smaller than standard conditional or unconditional CAPM and the model is not rejected by the data.

Suggested Citation

  • Francesco Franzoni & Tobias Adrian, 2005. "Learning about Beta: Time-varying factor loadings, expected returns, and the Conditional CAPM," Working Papers hal-00587579, HAL.
  • Handle: RePEc:hal:wpaper:hal-00587579
    Note: View the original document on HAL open archive server: https://hal-hec.archives-ouvertes.fr/hal-00587579
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    More about this item

    Keywords

    Asset Pricing; Bayesian Learning; CAPM Anomalies;
    All these keywords.

    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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