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Optimizing Benchmark-Based Utility Functions

Author

Listed:
  • David Morton
  • Elmira Popova
  • Ivilina Popova
  • Ming Zhong

Abstract

We Consider Four Utility Functions, Each Of Which Incorporates A Benchmark To Better Capture The Motivations Of Today's Portfolio Managers. Assuming Instrument Returns Are Normally Distributed, We Establish Conditions Under Which Optimal Portfolios For These Utilities Are Mean-Variance Efficient And We Briefly Discuss Computing Solutions Of The Models Via Standard Nonlinear Programming Tools. When Returns Are Not Normally Distributed, We Cannot, In General, Solve The Optimal Allocation Problems Exactly. Instead We Use An Approximation Procedure Rooted In Monte Carlo Simulation. Our Approach Requires Mixed-Integer Programming, And We Describe Computational Enhancements That Significantly Improve Our Ability To Solve These Models.

Suggested Citation

  • David Morton & Elmira Popova & Ivilina Popova & Ming Zhong, 2003. "Optimizing Benchmark-Based Utility Functions," Bulletin of the Czech Econometric Society, The Czech Econometric Society, vol. 10(18).
  • Handle: RePEc:czx:journl:v:10:y:2003:i:18:id:117
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    File URL: http://ces.utia.cas.cz/bulletin/index.php/bulletin/article/view/117
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    Citations

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    Cited by:

    1. Dmitriy Volinskiy & Michele Veeman & Wiktor Adamowicz, 2011. "Allocation of public funds to R&D: a portfolio choice-styled decision model and a biotechnology case study," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 34(2), pages 121-139, November.
    2. Morton, David P. & Popova, Elmira & Popova, Ivilina, 2006. "Efficient fund of hedge funds construction under downside risk measures," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 503-518, February.

    More about this item

    Keywords

    Portfolio Allocation; Mean-Variance Efficiency; Stochastic Programming; Monte Carlo Simulation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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