SOFTWARE AND INFORMATION SUPPORT FOR STOCK MARKET ASSET MANAGEMENT IN THE CONTEXT OF THE DIGITALIZATION OF FINANCIAL RELATIONSHIPS

Анотація

This study examines the nature, structure, and functional purpose of software and information systems for managing stock market assets in the context of the digitalization of financial relations. It is substantiated that in the modern financial environment, software and information support ceases to play a supporting technical role and transforms into a strategic resource that determines the quality of analytical support, the speed of response to market changes, the level of soundness of investment decisions, and the effectiveness of risk control. It is determined that its economic essence lies in transforming disparate information flows, market signals, and digital data into a systematized analytical foundation for the formation, evaluation, adjustment, and optimization of portfolio decisions. It has been demonstrated that the digitalization of the financial market is accompanied by an increase in the volume and speed of data circulation, the algorithmization of investment processes, and the development of robotic services, artificial intelligence, and platform-based interaction models, which necessitates the modernization of asset management tools. The main functions of software and information support have been systematized, including information storage, analytical, forecasting, control, optimization, risk-oriented, and reporting and regulatory functions. The structural elements of the system have been identified, encompassing data blocks and information sources, software integration platforms, analytical modules, and modules for portfolio modeling, risk management, monitoring, compliance, and data protection. It has been demonstrated that high-quality software and information support contributes to reducing information asymmetry, minimizing information risks, improving forecasting accuracy, and creating an information advantage for market participants. It has been determined that prospects for further development are linked to the implementation of explainable artificial intelligence, adaptive forecasting models, digital twins of financial processes, cloud architectures, API integrations, and hybrid asset management models that combine human expertise with machine analytics.

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