Comparison of performance of portfolio optimization methods

In this study, the use of Genetic Algorithm, Particle Swarm Optimization, Artificial Bee Colony and Differential Growth Algorithms from meta-heuristic algorithms in portfolio optimization is examined. Within the scope of the study, the first 25 stocks in the S&P 500 index and 30 companies in the BIST 30 index were optimized with the relevant meta-heuristic algorithms using daily return data between 03.01.2020 and 14.12.2022. As a result of the study, it is suggested that meta-heuristics are useful in portfolio optimization, but fundamental and technical analysis should also be considered, and portfolio diversification is also recommended. Finally, it is emphasized that the data used in the study covers only a certain period and future performances cannot be guaranteed