An application of Gray Wolf Optimization algorithm for fuzzy portfolio selection problem

Portfolio selection problem is an important issue in financial engineering which has been solved by a variety of heuristic and non-heuristic techniques. The most studies are concentrating on classical mean-variance model. In this paper, mean-variance model is extended to mean-variance-skewness model. The extended model is generally a high-dimensional nonlinear programming necessitating the use of efficient heuristics to find the solution. Hence, this paper presents a heuristic method named Gray Wolf Optimization (GWO) method. Finally, several numerical examples are provided to illustrate the modeling idea and performance and effectiveness of the proposed algorithm is compared against the exact approach (LINGO software) in terms of fitness value and required computational time. Results show that the proposed GWO is very promising and achieves quality results for fuzzy portfolio selection in a reasonable time..