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Beta Matrix and Common Factors in Stock Returns

Author

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  • Ahn, Seung C.
  • Horenstein, Alex R.
  • Wang, Na

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.

Suggested Citation

  • Ahn, Seung C. & Horenstein, Alex R. & Wang, Na, 2018. "Beta Matrix and Common Factors in Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1417-1440, June.
    • Handle: RePEc:cup:jfinqa:v:53:y:2018:i:03:p:1417-1440_00
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    Citations

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    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2019. "Too good to be true? Fallacies in evaluating risk factor models," Journal of Financial Economics, Elsevier, vol. 132(2), pages 451-471.
    2. Seung C. Ahn & Alex R. Horenstein, 2017. "Asset Pricing and Excess Returns over the Market Return," Working Papers 2017-12, University of Miami, Department of Economics.
    3. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Swiss Finance Institute Research Paper Series 23-44, Swiss Finance Institute.
    4. Alex R. Horenstein, 2021. "The Unintended Impact of Academic Research on Asset Returns: The Capital Asset Pricing Model Alpha," Management Science, INFORMS, vol. 67(6), pages 3655-3673, June.
    5. Sun, Yang & Zhang, Xuan & Zhang, Zhekai, 2022. "The reduced-rank beta in linear stochastic discount factor models," International Review of Financial Analysis, Elsevier, vol. 84(C).
    6. Yu Ren & Qin Wang, 2020. "Estimating the rank of a beta matrix: a GMM approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 4147-4173, December.

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