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Fuzzy portfolio selection model with real features and different decision behaviors

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Abstract

In the ever changing financial markets, investor’s decision behaviors may change from time to time. In this paper, we consider the effect of investor’s different decision behaviors on portfolio selection in fuzzy environment. We present a possibilistic mean-semivariance model for fuzzy portfolio selection by considering some real investment features including proportional transaction cost, fixed transaction cost, cardinality constraint, investment threshold constraints, decision dependency constraints and minimum transaction lots. To describe investor’s different decision behaviors, we characterize the return rates on securities by LR fuzzy numbers with different shape parameters in the left- and right-hand reference functions. Then, we design a novel hybrid differential evolution algorithm to solve the proposed model. Finally, we provide a numerical example to illustrate the application of our model and the effectiveness of the designed algorithm.

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Acknowledgements

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 (Nos. 2014A030310454 and 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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  1. School of Business Administration, South China University of Technology, Guangzhou, 510641, People’s Republic of China

    Yong-Jun Liu & Wei-Guo Zhang

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  1. Yong-Jun Liu
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  2. Wei-Guo Zhang
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Correspondence to Yong-Jun Liu.

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Liu, YJ., Zhang, WG. Fuzzy portfolio selection model with real features and different decision behaviors. Fuzzy Optim Decis Making 17, 317–336 (2018). https://doi.org/10.1007/s10700-017-9274-z

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