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Bayesian analysis of the factor model with finance applications

Author

Listed:
  • Sik-Yum Lee
  • Wai-Yin Poon
  • Xin-Yuan Song

Abstract

The factor analysis model has been widely applied to study finance problems. The purpose of this paper is to introduce a Bayesian approach for analysing the factor analysis model. The advantages of the proposed Bayesian approach over the classical maximum likelihood rest on its capability to incorporate additional prior information, to determine the number of factors in an objective manner, and to produce parameter and factor score estimates with good statistical properties. Based on recently developed tools in statistical computing, such as the Gibbs sampler and path sampling, methods for obtaining the Bayesian estimates of the parameters and factor scores, and a procedure for computing the Bayes factor for selecting the appropriate number of factors in the model, are developed. The proposed new methodologies are applied to analyse a data set taken from the Hong Kong stock security market. It is found that a three-factor model with a generic market factor can be used to describe the systematic components of asset returns.

Suggested Citation

  • Sik-Yum Lee & Wai-Yin Poon & Xin-Yuan Song, 2007. "Bayesian analysis of the factor model with finance applications," Quantitative Finance, Taylor & Francis Journals, vol. 7(3), pages 343-356.
    • Handle: RePEc:taf:quantf:v:7:y:2007:i:3:p:343-356
    DOI: 10.1080/14697680601009838
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    Cited by:

    1. Erol Muzir & Cevdet Kizil & Burak Ceylan, 2021. "Role of International Trade Competitive Advantage and Corporate Governance Quality in Predicting Equity Returns: Static and Conditional Model Proposals for an Emerging Market," JRFM, MDPI, vol. 14(3), pages 1-31, March.
    2. Yang, Qi & He, Haijin & Lu, Bin & Song, Xinyuan, 2022. "Mixture additive hazards cure model with latent variables: Application to corporate default data," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).

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