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Portfolio selection problem: a review of deterministic and stochastic multiple objective programming models

Author

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  • Meryem Masmoudi

    (University of Bahrain)

  • Fouad Ben Abdelaziz

    (NEOMA Business School)

Abstract

The literature on portfolio selection mostly concentrates on computational analysis rather than on modelling efforts. In response, this paper provides a comprehensive literature review of multiple objective deterministic and stochastic programming models for the portfolio selection problem. First, we summarize different concepts related to portfolio selection theory, including pricing models and portfolio risk measures. Second, we report the mathematical models that are generally used to solve deterministic and stochastic multiple objective programming problems. Finally, we present how these models can be used to solve the portfolio selection problem.

Suggested Citation

  • Meryem Masmoudi & Fouad Ben Abdelaziz, 2018. "Portfolio selection problem: a review of deterministic and stochastic multiple objective programming models," Annals of Operations Research, Springer, vol. 267(1), pages 335-352, August.
    • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-017-2466-7
    DOI: 10.1007/s10479-017-2466-7
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    References listed on IDEAS

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    7. Qi, Yue & Liao, Kezhi & Liu, Tongyang & Zhang, Yu, 2022. "Originating multiple-objective portfolio selection by counter-COVID measures and analytically instigating robust optimization by mean-parameterized nondominated paths," Operations Research Perspectives, Elsevier, vol. 9(C).
    8. Wu, Xu & Zhang, Linlin & Li, Jia & Yan, Ruzhen, 2021. "Fractal statistical measure and portfolio model optimization under power-law distribution," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

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