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Possibilistic Moment Models for Multi-period Portfolio Selection with Fuzzy Returns

Author

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  • Yong-Jun Liu

    (South China University of Technology)

  • Wei-Guo Zhang

    (South China University of Technology)

Abstract

The aim of this paper is to investigate the effects of higher moments on multi-period portfolio selection with fuzzy returns. This paper gives the definitions of possibilistic mean and variance about the product of multiple fuzzy numbers. Based on these definitions, three multi-period fuzzy portfolio optimization models are proposed. The proposed models aim to maximize terminal wealth and minimize terminal risk by taking into account some realistic constraints including higher moments, budget constraint, round-lot constraint, cardinality constraint and bound constraint. To ensure the selection of the best solutions, a novel fuzzy programming approach-based self-adaptive differential evolution algorithm is designed to solve the proposed models. A numerical example is given to demonstrate the application of the proposed models. Computational results show that the designed algorithm is effective for solving complex portfolio selection model with realistic constraints.

Suggested Citation

  • Yong-Jun Liu & Wei-Guo Zhang, 2019. "Possibilistic Moment Models for Multi-period Portfolio Selection with Fuzzy Returns," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1657-1686, April.
    • Handle: RePEc:kap:compec:v:53:y:2019:i:4:d:10.1007_s10614-018-9833-6
    DOI: 10.1007/s10614-018-9833-6
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    Cited by:

    1. Ameer Tamoor Khan & Xinwei Cao & Shuai Li, 2023. "Using Quadratic Interpolated Beetle Antennae Search for Higher Dimensional Portfolio Selection Under Cardinality Constraints," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1413-1435, December.

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