A concept of a model for forecasting indicators of share price changes to manage risk in non-financial organizations

V. A. Vostrov^a, M. A. Gorelikov^ab, M. E. Amelin<sup>c

a</sup> Surgut Branch of Scientific Research Institute for System Analysis of the National Research Centre “Kurchatov Institute”, Surgut, Russian Federation
^b LETI Saint Petersburg Electrotechnical University, Saint Petersburg, Russian Federation
^c Surgut State University, Surgut, Russian Federation

Abstract: We developed a framework for an intelligent model based on neural networks to support proactive management of financial risks in non-financial companies. We collected financial reporting data from disclosure websites, news feeds from verified sources, and market data through the Moscow Exchange (MOEX) API, which provides historical quotes, trades, positions of trading participants, and other information. We analyzed current practices and identified prerequisites for events that may influence the price dynamics of selected financial instruments. We designed and justified the model's architecture and selected solutions, taking into account the specific characteristics of the Russian market. The framework integrates multiple data sources to improve risk prediction and support decision-making in financial risk management.

Keywords: artificial intelligence methods, intelligent financial risk management models, AI-based investment management, artificial intelligence for finance.