Stock Portfolio Optimization Using Water Cycle Algorithm (Comparative Approach)

Abstract

Portfolio selection process is a subject focused by many researchers. Various criteria involved in this process have undergone alterations over time, necessitating the use of appropriate investment decision support tools. An optimization approach used in different sciences is using meta-heuristic algorithms. In the present study, using Water Cycle Algorithm (WCA), a model was introduced for selecting the optimal portfolio, and then the obtained results were compared with those obtained from Harmony Search (HS) and Imperialist Competitive Algorithm (ICA). For this purpose, using the data of 10-month (April 2016 to January 2017) returns of 50 top companies in the Stock Exchange Market of Iran, the optimal portfolio was estimated using the above-mentioned algorithms with the aim of maximizing profit and minimizing risk, and then the optimal portfolios obtained from these algorithms were compared with each other. Results of implementing these algorithms indicated that despite the high capability of the studied algorithms to optimize the portfolios, WCA algorithm had higher capability of portfolio optimization than the other ones