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

  • Yong-Jun LiuEmail author
  • Wei-Guo Zhang


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.


Multi-period portfolio selection Fuzzy set Higher moments Differential evolution 



This research was supported by the National Natural Science Foundation of China (Nos. 71501076 and 71720107002), the Natural Science Foundation of Guangdong Province of China (No. 2017A030312001), the Fundamental Research Funds for the Central Universities (No. 2017ZD102) and Guangzhou Financial Services Innovation and Risk Management Research Base.


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Business AdministrationSouth China University of TechnologyGuangzhouPeople’s Republic of China

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