Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/60587 
Year of Publication: 
2004
Series/Report no.: 
Staff Report No. 193
Publisher: 
Federal Reserve Bank of New York, New York, NY
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
JEL: 
G12
C11
Document Type: 
Working Paper

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