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Portfolio management with background risk under uncertain mean-variance utility

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  • Xiaoxia Huang

    (University of Science and Technology Beijing)

  • Guowei Jiang

    (University of Science and Technology Beijing)

Abstract

This paper studies comparative static effects in a portfolio selection problem when the investor has mean-variance preferences. Since the security market is complex, there exists the situation where security returns are given by experts’ estimates when they cannot be reflected by historical data. This paper discusses the problem in such a situation. Based on uncertainty theory, the paper first establishes an uncertain mean-variance utility model, in which security returns and background asset returns are uncertain variables and subject to normal uncertainty distributions. Then, the effects of changes in mean and standard deviation of uncertain background asset on capital allocation are discussed. Furthermore, the influence of initial proportion in background asset on portfolio investment decisions is analyzed when investors have quadratic mean-variance utility function. Finally, the economic analysis illustration of investment strategy is presented.

Suggested Citation

  • Xiaoxia Huang & Guowei Jiang, 2021. "Portfolio management with background risk under uncertain mean-variance utility," Fuzzy Optimization and Decision Making, Springer, vol. 20(3), pages 315-330, September.
    • Handle: RePEc:spr:fuzodm:v:20:y:2021:i:3:d:10.1007_s10700-020-09345-6
    DOI: 10.1007/s10700-020-09345-6
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    References listed on IDEAS

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    Cited by:

    1. Huang, Xiaoxia & Ma, Di & Choe, Kwang-Il, 2023. "Uncertain mean–variance portfolio model with inflation taking linear uncertainty distributions," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 203-217.
    2. Liu, Weilong & Zhang, Yong & Liu, Kailong & Quinn, Barry & Yang, Xingyu & Peng, Qiao, 2023. "Evolutionary multi-objective optimisation for large-scale portfolio selection with both random and uncertain returns," QBS Working Paper Series 2023/02, Queen's University Belfast, Queen's Business School.
    3. Yang, Tingting & Huang, Xiaoxia, 2022. "Two new mean–variance enhanced index tracking models based on uncertainty theory," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).

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