Beta Matrix and Common Factors in Stock Returns
Seung C. Ahn,
Alex Horenstein () and
Journal of Financial and Quantitative Analysis, 2018, vol. 53, issue 3, 1417-1440
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 Donaldâ€™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.
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