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Generalized mean semi-absolute deviation model of portfolio selection based on uncertainty theory

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  • Sanjoy Chhatri

    (National Institute of Technology Agartala)

  • Debasish Bhattacharya

    (National Institute of Technology Agartala)

  • Birojit Das

    (Amity University Kolkata)

Abstract

Portfolio selection problems, considering returns of the securities as uncertain variables, are an important area of contemporary research. In this line, linear and zigzag uncertainty distributions are popularly being used. These distributions contain two and three parameters, a, b and a, b, c, respectively. In this paper, two families of uncertainty distributions containing one arbitrary constant each have been introduced, and the properties are studied. Linear and zigzag uncertainty distributions then become a particular member of the respective family. This is achieved by introducing the arbitrary constants h and k, $$0 \le h

Suggested Citation

  • Sanjoy Chhatri & Debasish Bhattacharya & Birojit Das, 2025. "Generalized mean semi-absolute deviation model of portfolio selection based on uncertainty theory," Fuzzy Optimization and Decision Making, Springer, vol. 24(3), pages 431-456, September.
    • Handle: RePEc:spr:fuzodm:v:24:y:2025:i:3:d:10.1007_s10700-025-09452-2
    DOI: 10.1007/s10700-025-09452-2
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    References listed on IDEAS

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    1. Li, Bo & Zhang, Ranran, 2021. "A new mean-variance-entropy model for uncertain portfolio optimization with liquidity and diversification," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    2. Huang, Xiaoxia & Ying, Haiyao, 2013. "Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations," Economic Modelling, Elsevier, vol. 30(C), pages 61-66.
    3. Li, Xiang & Qin, Zhongfeng, 2014. "Interval portfolio selection models within the framework of uncertainty theory," Economic Modelling, Elsevier, vol. 41(C), pages 338-344.
    4. Qin, Zhongfeng, 2015. "Mean-variance model for portfolio optimization problem in the simultaneous presence of random and uncertain returns," European Journal of Operational Research, Elsevier, vol. 245(2), pages 480-488.
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