Portfolio Optimization Based on Complex Networks and Genetic Algorithms

Abstract

Portfolio optimization is a crucial endeavor in finance which aims to effectively manage investment risks and maximize returns. This paper explores the application of complex networks and genetic algorithms as a solution to the challenges associated with portfolio optimization. This paper strives to optimize the composition of portfolios, mitigate risks, and enhances potential returns by analyzing the interdependencies and correlations among financial assets using complex networks and utilizing genetic algorithms as an optimization technique. The results demonstrate that the portfolio resulting from the optimization of genetic algorithms applied to complex networks exhibits remarkable risk control capabilities. This integrated approach effectively minimizes risks associated with investments, contributing to the creation of a more stable and resilient portfolio, particularly in volatile financial markets.