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Fuzzy chance-constrained goal programming model for multi-attribute financial portfolio selection

Author

Listed:
  • Laila Messaoudi

    (Faculté des Sciences Economiques et de Gestion de Sfax)

  • Belaid Aouni

    (Qatar University)

  • Abdelwaheb Rebai

    (Faculté des Sciences Economiques et de Gestion de Sfax)

Abstract

The aim of this paper is to propose a fuzzy chance constrained goal programming model for solving a multi-attribute financial portfolio selection problem under two types of uncertainty namely randomness and fuzziness. The chance-constrained goals are considered as random variables. The obtained portfolio through this model is the portfolio of the best compromise where the financial decision-maker was asked to make tradeoffs among conflicting and incommensurable attributes such as the expected return, risk and the earning price ratio. The proposed model has been applied to the Tunisian stock exchange market for the period July 2003 to December 2007.

Suggested Citation

  • Laila Messaoudi & Belaid Aouni & Abdelwaheb Rebai, 2017. "Fuzzy chance-constrained goal programming model for multi-attribute financial portfolio selection," Annals of Operations Research, Springer, vol. 251(1), pages 193-204, April.
    • Handle: RePEc:spr:annopr:v:251:y:2017:i:1:d:10.1007_s10479-015-1937-y
    DOI: 10.1007/s10479-015-1937-y
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    References listed on IDEAS

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    1. Szego, Giorgio, 2005. "Measures of risk," European Journal of Operational Research, Elsevier, vol. 163(1), pages 5-19, May.
    2. Aouni, Belaid & Colapinto, Cinzia & La Torre, Davide, 2014. "Financial portfolio management through the goal programming model: Current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 234(2), pages 536-545.
    3. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
    4. Golany, B. & Kress, M., 1993. "A multicriteria evaluation of methods for obtaining weights from ratio-scale matrices," European Journal of Operational Research, Elsevier, vol. 69(2), pages 210-220, September.
    5. Arenas Parra, M. & Bilbao Terol, A. & Rodriguez Uria, M. V., 2001. "A fuzzy goal programming approach to portfolio selection," European Journal of Operational Research, Elsevier, vol. 133(2), pages 287-297, January.
    6. Aouni, Belaid & Ben Abdelaziz, Foued & Martel, Jean-Marc, 2005. "Decision-maker's preferences modeling in the stochastic goal programming," European Journal of Operational Research, Elsevier, vol. 162(3), pages 610-618, May.
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    Cited by:

    1. Masoud Rahiminezhad Galankashi & Farimah Mokhatab Rafiei & Maryam Ghezelbash, 2020. "Portfolio selection: a fuzzy-ANP approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-34, December.
    2. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    3. Mila Bravo & Dylan Jones & David Pla-Santamaria & Francisco Salas-Molina, 2022. "Encompassing statistically unquantifiable randomness in goal programming: an application to portfolio selection," Operational Research, Springer, vol. 22(5), pages 5685-5706, November.

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