Beta Matrix and Common Factors in Stock Returns

Seung Ahn, Alex R. Horenstein, Na Wang

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1417-1440
Number of pages24
JournalJournal of Financial and Quantitative Analysis
Issue number3
StatePublished - Jun 1 2018

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics


Dive into the research topics of 'Beta Matrix and Common Factors in Stock Returns'. Together they form a unique fingerprint.

Cite this