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

Subject Areas : Fuzzy Optimization and Modeling Journal

MariehAlsadat MirAboalhassani ¹ , Farzad Movahedi Sobhani ² , Emran Mohammadi ³

1 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Received: 2022-01-12 Accepted : 2022-03-07 Published : 2022-01-01

Keywords: Value at Risk, Meta-Heuristic Algorithms, Conditional Value at Risk, Fuzzy uncertainty,

Abstract :

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.