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Uncertain random portfolio optimization via semi-variance

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Abstract

Semi-variance is a similar measure to variance, but it only considers values that are below the expected value. As important roles of semi-variance in finance, this paper proposes the concept of semi-variance for uncertain random variables. Also, a computational approach for semi-variance is provided via inverse uncertainty distribution. As an application in finance, portfolio selection problems of uncertain random returns are solved by minimizing semi-variance in mean-semi variance models. For better illustration, mean-semi variance model is compared with mean-variance one. Finally, for better understanding, some tables, figures and outputs are provided.

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Author information

Authors and Affiliations

  1. College of Systems Engineering, National University of Defense Technology, Changsha, 410073, China

    Guangquan Cheng

  2. Department of Statistics, University of Sistan and Baluchestan, Zahedan, Iran

    Hamed Ahmadzade

  3. Department of Statistics, Payame Noor University, 19395-4697, Tehran, Iran

    Mehran Farahikia & Masoud Yarmohammadi

Authors
  1. Guangquan Cheng
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  2. Hamed Ahmadzade
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  3. Mehran Farahikia
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  4. Masoud Yarmohammadi
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Contributions

Conceptualization, GC; formal analysis, HA; methodology, HA; resources, MY; software, MF; writing original draft, HA; funding acquisition, GC. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Hamed Ahmadzade.

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The authors declare no conflict of interest.

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Cheng, G., Ahmadzade, H., Farahikia, M. et al. Uncertain random portfolio optimization via semi-variance. Int. J. Mach. Learn. & Cyber. 13, 2533–2543 (2022). https://doi.org/10.1007/s13042-022-01542-6

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  • DOI: https://doi.org/10.1007/s13042-022-01542-6

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