Research on the Potential Use of Artificial Intelligence Systems for Automating Decision-Making in Markowitz Portfolio Formation

Modern financial markets immerse analysts in a whirlwind of vast data volumes, rapid changes, and high uncertainty. These conditions necessitate more flexible approaches than traditional methods. This paper explores the application of artificial intelligence (AI) systems for automating processes related to the Markowitz model in the context of big data analysis. Central to the study is the LSTM machine learning algorithm, which can more accurately predict asset returns and optimize portfolios. The presented results demonstrate that integrating AI significantly enhances adaptability and efficiency in risk management in turbulent market environments.