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Multi-objective stochastic programming for portfolio selection

Authors
Journal
European Journal of Operational Research
0377-2217
Publisher
Elsevier
Publication Date
Volume
177
Issue
3
Identifiers
DOI: 10.1016/j.ejor.2005.10.021
Keywords
  • Goal Programming
  • Compromise Programming
  • Chance Constrained Programming
  • Chance Constrained Compromise Programming
  • Portfolio Selection
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract Generally, in the portfolio selection problem the Decision Maker (DM) considers simultaneously conflicting objectives such as rate of return, liquidity and risk. Multi-objective programming techniques such as goal programming (GP) and compromise programming (CP) are used to choose the portfolio best satisfying the DM’s aspirations and preferences. In this article, we assume that the parameters associated with the objectives are random and normally distributed. We propose a chance constrained compromise programming model (CCCP) as a deterministic transformation to multi-objective stochastic programming portfolio model. CCCP is based on CP and chance constrained programming (CCP) models. The proposed program is illustrated by means of a portfolio selection problem from the Tunisian stock exchange market.

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