An End-User Decision Support System for Portfolio Selection: A Goal Programming Approach with an Application to Kuwait Stock Exchange (KSE)

Abstract

The focus of this papere is to present an intuitive enduser Decision Support System (DSS) for portfolio selection based on Mean-Variance (M-V) Model of portfolio selection by Markowitz [1952, 1991]. The DSS utilizes a Goal Linear Programming (GLP) model for fulfiling the investor’s objectives and preferences in terms rate of return, risk and asset allocation and diversification in order to reach an optimum solution. The DSS reported is flexiable enough and could be extended through goal extension, extending the goal achievement requirements by adding more goals and using other models within the computation intelligence paradigm such ANN, Fuzzy, Rough Sets, Genetic Algorithm (GA), etc. The DSS is implement within an objective-oriented paradigm using Microsoft VB.NET. The implementation of the GLP model for the portfolio selection was done using the Extended Large-Scale LP/QP Solver within Solver Platform SDK from Frontline Systems, Inc. ( www.solver.com).