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A multiple stochastic goal programming approach for the agent portfolio selection problem

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  • Hatem Masri

    (University of Bahrain)

Abstract

Stochastic goal programming is a suitable solution approach for multi-objective stochastic programs when a unique goal is settled for each objective function. In this paper, we address the case of multiple stochastic goals for an objective function. We derive results from studying the agent portfolio selection problem. The proposed multiple stochastic goal programming approach allows investors to set different goals for the return objective function. A chance constrained approach is proposed to address the stochastic investors’ minimum acceptable rate of return and a recourse approach to deal with investors’ ideal rate of return. An empirical study from Bahrain stock market is reported.

Suggested Citation

  • Hatem Masri, 2017. "A multiple stochastic goal programming approach for the agent portfolio selection problem," Annals of Operations Research, Springer, vol. 251(1), pages 179-192, April.
    • Handle: RePEc:spr:annopr:v:251:y:2017:i:1:d:10.1007_s10479-015-1884-7
    DOI: 10.1007/s10479-015-1884-7
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    References listed on IDEAS

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    Cited by:

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    4. 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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