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A Decision Theory Approach to Portfolio Selection

Author

Listed:
  • James C. T. Mao

    (Professor of Finance, The University of Michigan)

  • Carl Erik Särndal

    (Visiting Lecturer in Statistics, The University of Michigan)

Abstract

This paper starts with a brief summary of Harry Markowitz's portfolio selection model and proceeds to reformulate it within the framework of modern statistical decision theory. The future returns from securities are viewed as a function of the unknown state of nature. The investor has certain a priori probabilities for the different states of nature, which probabilities he later modifies in the light of new experimental information. Following the Bayesian strategy, the investor chooses that portfolio of securities which maximizes the weighted average of payoffs, using as weights the a posteriori probabilities of the states of nature. A computer program, based on the critical line method, is used to solve a simple illustrative problem.

Suggested Citation

  • James C. T. Mao & Carl Erik Särndal, 1966. "A Decision Theory Approach to Portfolio Selection," Management Science, INFORMS, vol. 12(8), pages 323-333, April.
    • Handle: RePEc:inm:ormnsc:v:12:y:1966:i:8:p:b323-b333
    DOI: 10.1287/mnsc.12.8.B323
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    Cited by:

    1. Soyer, Refik & Tanyeri, Kadir, 2006. "Bayesian portfolio selection with multi-variate random variance models," European Journal of Operational Research, Elsevier, vol. 171(3), pages 977-990, June.

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