RISK MANAGEMENT AS A KEY BUSINESS PROCESS OF THE STOCK MARKET

Abstract

The purpose of the study is to analyze the modern risks of the stock market functioning in the conditions of digitalization of the economy and the development of artificial intelligence technologies, as well as to evaluate the effectiveness of traditional and modern risk management methods to ensure the stability of the financial system and increase the efficiency of investment activities. Special attention is paid to the transformation of risk management under the influence of digital technologies, algorithmic trading, ESG factors and AI-driven systems. In the research process, a complex of general scientific and special methods was used, including methods of analysis and synthesis, comparative analysis, systematization, generalization and tabular presentation of data. To evaluate modern approaches to risk management, traditional financial tools such as Value-at-Risk (VaR), Expected Shortfall (ES), scenario analysis and stress testing, as well as modern digital technologies based on machine learning, Natural Language Processing (NLP) and agent artificial intelligence, were analyzed. It was established that in 2025-2026 market, systemic, cyber and ESG risks have the greatest impact on the functioning of the stock market. It was determined that the digitalization of the financial sector contributes to the emergence of new risks, in particular algorithmic, model and cyber threats. It has been proven that traditional methods of risk management remain important risk assessment tools, but have limitations in conditions of high volatility and rapid changes in the market environment. At the same time, modern AI technologies provide increased accuracy of risk forecasting, real-time data analysis, and automation of portfolio management and hedging processes. It is substantiated that the most effective approach to risk management in the modern stock market is a combination of traditional financial models with digital technologies and artificial intelligence tools. The integration of AI solutions into the risk management system contributes to increasing the stability of the stock market, the efficiency of investment decision-making and the adaptation of the financial system to new global challenges.