Portfolio Optimization Using the Whale Algorithm with Expected Shortfall as the Measure of Risk

Portfolio Selection is one of the most important decisions that institutional investors have to face. Markowitz was the first to introduce risk into the portfolio selection decision by introducing the Mean-Variance Model. This created one of the most important fields in finance, that is Portfolio Optimization and finding the efficient frontier. In the next researches, adding real world constraints to the model broadened this field. With increasing the number of assets or the constraints, Portfolio Optimization becomes an NP-hard problem which is impossible to solve with derivative-based methods, therefore, numerical and metaheuristic methods should be used for solving it. The aim of this research is optimizing portfolio using Whale optimization algorithm. This metaheuristic algorithm is inspired by the behavior of Whales and was introduced in 2016. This research implements the algorithm in the top 50 index in Tehran Stock Exchange and tries to find the efficient portfolio in this index. We also compare the performance of this method to two other metaheuristic algorithms and explain the advantages of the proposed method in portfolio optimization.