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

• Main Authors: Jun Zhang, Qian Li
• Format: Article
• Language: English
• Published: MDPI AG 2019-09-01
• Series: Entropy
• Subjects: background risk; fuzzy semi-entropy; multi-period portfolio selection; dragonfly algorithm; credibility theory
• Online Access: https://www.mdpi.com/1099-4300/21/10/944

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.