Mean-Semi-Entropy Models of Fuzzy Portfolio Selection

In this paper, a concept of fuzzy semientropy is proposed to quantify the downside uncertainty. Several properties of fuzzy semientropy are identified and interpreted. By quantifying the downside risk with the use of semientropy, two mean-semi-entropy portfolio selection models are formulated, and a...

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Bibliographic Details
Published inIEEE transactions on fuzzy systems Vol. 24; no. 6; pp. 1627 - 1636
Main Authors Zhou, Jiandong, Li, Xiang, Pedrycz, Witold
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Analytical models
Biological system modeling
Entropy
Fuzzy semientropy
Genetic algorithms
Investment
mean-semi-entropy model
portfolio selection
Portfolios
Security
Stock exchanges
Uncertainty
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ISSN1063-6706
1941-0034
DOI10.1109/TFUZZ.2016.2543753

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Summary:In this paper, a concept of fuzzy semientropy is proposed to quantify the downside uncertainty. Several properties of fuzzy semientropy are identified and interpreted. By quantifying the downside risk with the use of semientropy, two mean-semi-entropy portfolio selection models are formulated, and a fuzzy simulation-based genetic algorithm is designed to solve the models to optimality. We carry out comparative analyses among the fuzzy mean-entropy models and the fuzzy mean-semi-entropy models and demonstrate that the mean-semi-entropy models can significantly improve the dispersion of investment. Several illustrative examples using stock dataset from the real-world financial market (China Shanghai Stock Exchange) also show the effectiveness of the models.
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ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2016.2543753