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Using Bayesian Variable Selection Methods to Choose Style Factors in Global Stock Return Models

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Author Info
Anthony Hall (University of Technology)
Soosung Hwang (City University Business School)
Stephen E. Satchell (Trinity College)

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Abstract

This paper applies Bayesian variable selection methods from the statistics literature to give guidance in the decision to include/omit factors in a global (linear factor) stock return model. Once one has accounted for country and sector, it is possible to see which style or styles best explains current asset returns. The study suggests that global style is not an important component once country and sector have been accounted for.

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File URL: http://fmwww.bc.edu/RePEc/es2000/1213.pdf
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Publisher Info
Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1213.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:1213

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  1. Smith, M. & Kohn, R., 1998. "Nonparametric Seemingly Unrelated Regression," Monash Econometrics and Business Statistics Working Papers 7/98, Monash University, Department of Econometrics and Business Statistics.
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  2. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December. [Downloadable!] (restricted)
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  3. Kuo, G. W. & Satchell, S. E., 1998. "Global Equity Styles and Industry Effects: Portfolio Construction via Dummy Variables," Cambridge Working Papers in Economics 9807, Faculty of Economics, University of Cambridge.
  4. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70. [Downloadable!] (restricted)
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This page was last updated on 2009-12-2.

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