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Entropy 2015, 17(5), 3319-3331; doi:10.3390/e17053319

A Mean-Variance Hybrid-Entropy Model for Portfolio Selection with Fuzzy Returns

School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
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Academic Editor: Kevin H. Knuth
Received: 4 February 2015 / Accepted: 20 April 2015 / Published: 14 May 2015
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Abstract

In this paper, we define the portfolio return as fuzzy average yield and risk as hybrid-entropy and variance to deal with the portfolio selection problem with both random uncertainty and fuzzy uncertainty, and propose a mean-variance hybrid-entropy model (MVHEM). A multi-objective genetic algorithm named Non-dominated Sorting Genetic Algorithm II (NSGA-II) is introduced to solve the model. We make empirical comparisons by using the data from the Shanghai and Shenzhen stock exchanges in China. The results show that the MVHEM generally performs better than the traditional portfolio selection models. View Full-Text
Keywords: portfolio selection; fuzzy returns; hybrid entropy; multi-objective genetic algorithm; Markov prediction portfolio selection; fuzzy returns; hybrid entropy; multi-objective genetic algorithm; Markov prediction
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zhou, R.; Zhan, Y.; Cai, R.; Tong, G. A Mean-Variance Hybrid-Entropy Model for Portfolio Selection with Fuzzy Returns. Entropy 2015, 17, 3319-3331.

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