Beta Matrix and Common Factors in Stock Returns

Seung Ahn, Alex R. Horenstein, Na Wang

Research output: Contribution to journalReview article

2 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1417-1440
Number of pages24
JournalJournal of Financial and Quantitative Analysis
Volume53
Issue number3
DOIs
StatePublished - Jun 1 2018

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Estimator
Stock returns
Common factors
Simulation
Bayesian information criterion
Assets
Asset pricing models
Multifactor model
Risk premium

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

Cite this

Beta Matrix and Common Factors in Stock Returns. / Ahn, Seung; Horenstein, Alex R.; Wang, Na.

In: Journal of Financial and Quantitative Analysis, Vol. 53, No. 3, 01.06.2018, p. 1417-1440.

Research output: Contribution to journalReview article

Ahn, Seung ; Horenstein, Alex R. ; Wang, Na. / Beta Matrix and Common Factors in Stock Returns. In: Journal of Financial and Quantitative Analysis. 2018 ; Vol. 53, No. 3. pp. 1417-1440.
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