Fuzzy Portfolio Optimization Using Credibility Theory: Multi-Objective Evolutionary Optimization Algorithms

Fuzzy Optimization and Modeling Journal

مقاله 4، دوره 3، شماره 1، فروردین 2022، صفحه 41-63   

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.30495/fomj.2022.1949727.1054

نویسندگان

MariehAlsadat MirAboalhassani¹؛ Farzad Movahedi Sobhani^{* 1}؛ Emran Mohammadi²

¹Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

²School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

چکیده

Investors are always interested to choose the portfolio with the highest return and lowest risk for optimal asset management. A multi-objective portfolio optimization problem with cardinality constraint that determines the number of assets in a portfolio is considered in this paper. Objectives are maximizing the expected value of wealth and minimizing value at risk and conditional value at risk. Due to the complexity of the problem, it is necessary to use meta-heuristic algorithms. We use multi-objective evolutionary algorithms (Multi-Objective Particle Swarm Optimization, Non-Dominated Sorting Genetic Algorithm-II) to overcome this problem. In this research, the liquidity constraint and the thresholds of investments are considered. We use experts’ opinions in a fuzzy method to deal with the uncertainties in the parameters and provide better and more quality decisions. Finally, an Iranian stock market case study is presented to examine the proposed model in various situations. The results indicate that examining uncertainties and other real-world assumptions provides more efficient and practical solutions.

کلیدواژه‌ها

Value at Risk؛ Conditional Value at Risk؛ Fuzzy Uncertainty؛ Meta-Heuristic Algorithms