Modern methods of risk management in Ukrainian energy markets

In the context of rapid technological development and increasing instability on global markets, the issue of developing effective risk management methods on Ukrainian energy markets becomes particularly important. Modern risk management methods include the use of machine learning algorithms to predict and minimize potential threats. This study focuses on the implementation of innovative machine learning and artificial intelligence technologies to anticipate risks in energy markets and respond timely to potential stresses. This paper explores the development of intelligent risk management systems that apply deep learning neural network technologies for predicting market indicators. These systems provide detailed analysis of large data sets, opening new perspectives for the accurate identification of risk factors. The study involved analysis of historical data and assessment of current market trends, which allowed the development of a comprehensive approach to identifying price volatility in risky market segments. Results showed that the application of machine learning algorithms and artificial intelligence methods can significantly enhance the accuracy of risk prediction and optimize decision-making processes. It was found that intelligent systems with artificial intelligence elements enhance the understanding of market mechanisms and enable government officials, regulatory bodies, and management of energy companies to make more informed and effective management decisions. The findings indicate a great potential for the application of artificial intelligence and machine learning in risk management on energy markets. Utilizing these technologies can significantly reduce risks and enhance stability in resource management under unpredictability, which is key to ensuring long-term success in the field.