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On Comparing Asset Pricing Models

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  • SIDDHARTHA CHIB
  • XIAMING ZENG
  • LINGXIAO ZHAO

Abstract

Revisiting the framework of (Barillas, Francisco, and Jay Shanken, 2018, Comparing asset pricing models, The Journal of Finance 73, 715–754). BS henceforth, we show that the Bayesian marginal likelihood‐based model comparison method in that paper is unsound : the priors on the nuisance parameters across models must satisfy a change of variable property for densities that is violated by the Jeffreys priors used in the BS method. Extensive simulation exercises confirm that the BS method performs unsatisfactorily. We derive a new class of improper priors on the nuisance parameters, starting from a single improper prior, which leads to valid marginal likelihoods and model comparisons. The performance of our marginal likelihoods is significantly better, allowing for reliable Bayesian work on which factors are risk factors in asset pricing models.

Suggested Citation

  • Siddhartha Chib & Xiaming Zeng & Lingxiao Zhao, 2020. "On Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 75(1), pages 551-577, February.
    • Handle: RePEc:bla:jfinan:v:75:y:2020:i:1:p:551-577
    DOI: 10.1111/jofi.12854
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    Cited by:

    1. Doron Avramov & Si Cheng & Lior Metzker & Stefan Voigt, 2023. "Integrating Factor Models," Journal of Finance, American Finance Association, vol. 78(3), pages 1593-1646, June.
    2. Hollstein, Fabian & Prokopczuk, Marcel, 2022. "Testing Factor Models in the Cross-Section," Journal of Banking & Finance, Elsevier, vol. 145(C).
    3. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    4. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    5. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
    6. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    7. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.
    8. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    9. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    10. Massa, Massimo & O'Donovan, James & Zhang, Hong, 2022. "International asset pricing with strategic business groups1," Journal of Financial Economics, Elsevier, vol. 145(2), pages 339-361.
    11. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    12. Massa, Massimo & O'Donovan, James & Zhang, Hong, 2021. "International Asset Pricing with Strategic Business Groups," CEPR Discussion Papers 15746, C.E.P.R. Discussion Papers.
    13. Qiao, Zhuo & Wang, Yan & Lam, Keith S.K., 2022. "New evidence on Bayesian tests of global factor pricing models," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 160-172.

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