A new MOPSO to solve a multi-objective portfolio selection model with fuzzy value-at-risk

Abstract

This study proposes an novel fuzzy multi-objective model that can evaluate the invest risk properly and increase the probability of obtaining the expected return. In building the model, fuzzy Value-at-Risk is used to evaluate the exact future risk, in term of loss. And, variance is utilized to make the selection more stable. This model can provide investors with more significant information in decision-making. To solve this model, a new Pareto-optimal set based multi-objective particle swarm optimization algorithm is designed to obtain better solutions among the Pareto-front. At the end of this study, the proposed model and algorithm are exemplified by one numerical example. Experiment results show that the model and algorithm are effective in solving the multi-objective portfolio selection problem. © 2011 Springer-Verlag.