Multi-objective stochastic programming for portfolio selection

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...

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Bibliographic Details
Published in:European journal of operational research Vol. 177; no. 3; pp. 1811 - 1823
Main Authors: Abdelaziz, Fouad Ben, Aouni, Belaid, Fayedh, Rimeh El
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 16.03.2007
Elsevier
Elsevier Sequoia S.A
Series:European Journal of Operational Research
Subjects:
Chance constrained compromise programming
Chance constrained programming
Compromise programming
Decision making models
Goal programming
Portfolio management
Portfolio selection
Stock exchanges
Studies
Tunisia
Chance constrained compromise programming
Portfolio selection
Chance constrained programming
Goal programming
Compromise programming
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary: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.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2005.10.021