Portfolio Optimization Using a Combined Model of Fuzzy Network Analytic Process: An Approach Based on Similarity and Genetic Algorithm

Abstract

Portfolio management has always been an issue of high importance in financial markets.This paper is an attempt to introduce a new technique of portfolio selection. After presenting a review of literature on factors influencing portfolio selection, the importance of each factor is determined in regards to experts' opinions and a weight is assigned to each factor using fuzzy network analytic process technique. Consequently, using an approach based on TOPSIS and similarity, selected stocks were ranked. After depicting efficient frontiers of the top ranks obtained from both approaches, using genetic algorithm, Sharpe ratio was used in order to examine model's performance.