Abstract
This scientific article is devoted to the actual topic of application of artificial intelligence for risk analysis in the securities market. The article considers the role of artificial intelligence in analyzing data, identifying potential risks and making informed investment decisions. The research methodology is based on theoretical and empirical methods, as well as the results of domestic scientific research. The results of the study emphasize the importance of understanding and managing risk in financial markets, including the concept of portfolio and systemic risk. The author analyzes various methods of risk analysis, including statistical models, fundamental analysis, technical analysis, scenario analysis, and machine learning methods. Special attention is given to the application of neural networks, genetic algorithms, and other artificial intelligence techniques to improve price forecasting, optimal portfolio determination, and risk management. The conclusion emphasizes the promising direction of using artificial intelligence in financial analytics, but notes the need to consider potential challenges and limitations, such as market volatility, data availability and quality, interpretability of models, and ethical considerations.
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