Optimizing Benchmark-Based Utility Functions
AbstractWe 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.
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Bibliographic InfoArticle provided by The Czech Econometric Society in its journal Bulletin of the Czech Econometric Society.
Volume (Year): 10 (2003)
Issue (Month): 18 ()
Portfolio Allocation; Mean-Variance Efficiency; Stochastic Programming; Monte Carlo Simulation;
Find related papers by 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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