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Portfolio Choice under Parameter Uncertainty: Bayesian Analysis and Robust Optimization Comparison

Author

Listed:
  • António Alberto Santos

    (Faculty of Economics, University of Coimbra and GEMF, Portugal)

  • Ana Margarida Monteiro

    (Faculty of Economics, University of Coimbra and GEMF, Portugal)

  • Rui Pascoal

    (Faculty of Economics, University of Coimbra, Portugal)

Abstract

Parameter uncertainty has been a recurrent subject treated in the financial literature. The normative portfolio selection approach considers two main kinds of decision rules: expected expected utility maximization and mean-variance criterion. Assuming that the mean-variance criterion is a good approximation to the expected utility maximization paradigm, a major factor of concern is parameter uncertainty which, when it is not taken into account, can lead to meaningless portfolios. A statistical approach, based on a Bayesian analysis, can be applied to parameter uncertainty. This can be compared with a robust optimization approach where it is assumed that the value of the unknown parameters can change within a given region. Comparisons over these two approaches are performed in this paper. We consider two measures to quantify the effects of the estimation risk, one of the measures is new and extends an existing one. The results allows us to distinguish the approaches and select the one that implies lower mean losses.

Suggested Citation

  • António Alberto Santos & Ana Margarida Monteiro & Rui Pascoal, 2014. "Portfolio Choice under Parameter Uncertainty: Bayesian Analysis and Robust Optimization Comparison," GEMF Working Papers 2014-25, GEMF, Faculty of Economics, University of Coimbra.
    • Handle: RePEc:gmf:wpaper:2014-25.
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    portfolio choice; Bayesian statistics; robust optimization; conic programming; semidefinite programming; loss distribution.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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