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A Goal Programming Model with Satisfaction Function for Risk Management and Optimal Portfolio Diversification

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  • Davide La Torre
  • Marco Maggis

Abstract

We extend the classical risk minimization model with scalar risk measures to the general case of set-valued risk measures. The problem we obtain is a set-valued optimization model and we propose a goal programming-based approach with satisfaction function to obtain a solution which represents the best compromise between goals and the achievement levels. Numerical examples are provided to illustrate how the method works in practical situations.

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  • Davide La Torre & Marco Maggis, 2012. "A Goal Programming Model with Satisfaction Function for Risk Management and Optimal Portfolio Diversification," Papers 1201.1783, arXiv.org, revised Sep 2012.
    • Handle: RePEc:arx:papers:1201.1783
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    References listed on IDEAS

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    Cited by:

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