Beta Matrix and Common Factors in Stock Returns

Seung C. Ahn, Alex Horenstein and Na Wang

Journal of Financial and Quantitative Analysis, 2018, vol. 53, issue 3, 1417-1440

Abstract: We consider the estimation methods for the rank of a beta matrix corresponding to a multifactor model and study which method would be appropriate for data with a large number of assets. Our simulation results indicate that a restricted version of Cragg and Donald’s (1997) Bayesian information criterion estimator is quite reliable for such data. We use this estimator to analyze some selected asset pricing models with U.S. stock returns. Our results indicate that the beta matrix from many models fails to have full column rank, suggesting that risk premiums in these models are underidentified.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:cup:jfinqa:v:53:y:2018:i:03:p:1417-1440_00

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