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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