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Credibilistic Mean-Semi-Entropy Model for Multi-Period Portfolio Selection with Background Risk

by Jun Zhang and Qian Li *
School of Management and Engineering, Capital University of Economics and Business, Beijing 100010, China
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(10), 944; https://doi.org/10.3390/e21100944
Received: 4 September 2019 / Revised: 23 September 2019 / Accepted: 24 September 2019 / Published: 26 September 2019
In financial markets, investors will face not only portfolio risk but also background risk. This paper proposes a credibilistic multi-objective mean-semi-entropy model with background risk for multi-period portfolio selection. In addition, realistic constraints such as liquidity, cardinality constraints, transaction costs, and buy-in thresholds are considered. For solving the proposed multi-objective problem efficiently, a novel hybrid algorithm named Hybrid Dragonfly Algorithm-Genetic Algorithm (HDA-GA) is designed by combining the advantages of the dragonfly algorithm (DA) and non-dominated sorting genetic algorithm II (NSGA II). Moreover, in the hybrid algorithm, parameter optimization, constraints handling, and external archive approaches are used to improve the ability of finding accurate approximations of Pareto optimal solutions with high diversity and coverage. Finally, we provide several empirical studies to show the validity of the proposed approaches. View Full-Text
Keywords: background risk; fuzzy semi-entropy; multi-period portfolio selection; dragonfly algorithm; credibility theory background risk; fuzzy semi-entropy; multi-period portfolio selection; dragonfly algorithm; credibility theory
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Zhang, J.; Li, Q. Credibilistic Mean-Semi-Entropy Model for Multi-Period Portfolio Selection with Background Risk. Entropy 2019, 21, 944.

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