Learning about beta: a new look at CAPM tests

Tobias Adrian () and Francesco Franzoni

No 193, Staff Reports from Federal Reserve Bank of New York

Abstract: When risk-factor loadings are time-varying and unobservable, investors are forced to form beliefs about the levels of their loadings. The learning process involved in forming these beliefs has normative implications for asset-pricing tests. This paper develops an equilibrium model of learning about time-varying beta. In the model, the capital asset pricing model (CAPM) works for investors' probability distribution. However, mis-pricing can be observed if econometricians estimate betas without accounting for the investors' learning process. The empirical implication for asset-pricing tests is that the factor loadings must be estimated as latent variables. We provide an empirical application of this methodology to the cross section of returns on ten book-to-market and ten size-sorted portfolios. For these assets, the data do not reject a learning-augmented version of CAPM. This model performs better than other common empirical specifications, including the Fama-French three-factor model.

Keywords: Capital assets pricing model; Investments (search for similar items in EconPapers)
Date: Written 2004
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