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SPEPS Preprint

Author(s): Csaba I. Fabian, Eötvös University
Gautam Mitra, Brunel University
Diana Roman, Brunel University
Title: Processing Second-Order Stochastic Dominance models using cutting-plane representations
Date of Acceptance: 02.07.2008
Submission Date: 28.01.2008
Series Title: Stochastic Programming E-Print Series
(SPEPS)
Editors: Julie L. Higle; Werner Römisch; Surrajeet Sen
Complete Preprint: pdf (urn:nbn:de:kobv:11-10090085)
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Abstract (eng):
Second-order stochastic dominance (SSD) is widely recognised as an important decision criteria in portfolio selection. Unfortunately, stochastic dominance models can be very demanding from a computational point of view. In this paper we consider two types of models which use SSD as a choice criterion. The first, proposed by Dentcheva and Ruszczyski (2006), uses a SSD constraint, which can be written as a set of integrated chance constraints (ICCs). The second, proposed by Roman, Darby-Dowman, and Mitra (2006) uses SSD through a multi-objective formulation with CVaR objectives. Cutting plane representations and algorithms were proposed by Klein Haneveld and van der Vlerk (2006) for ICCs, and by Künzi-Bay and Mayer (2006) for CVaR minimization. These concepts are taken into consideration to propose representations and solution methods for the above class of SSD based models. We describe a cutting plane based solution algorithm and give implementation details. A computational study is presented, which demonstrates the effectiveness and the scale-up properties of the solution algorithm, as applied to the SSD model of Roman, Darby-Dowman, and Mitra (2006).
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