Modeling financial market conditions in an intelligent economy based on a fuzzy set approach

 In the era of globalization, there is a high degree of interconnection between a country's economy and the state of its financial sector. Effective functioning and dynamic development of the financial sector become an urgent need for ensuring stable economic growth. However, quite often, many developing countries on their path to this development face a series of constraints. These restrictions can seriously affect their financial potential, hindering the development of financial systems. Given these factors, the importance of overcoming them and searching and developing the latest innovative methods for analyzing financial phenomena and processes comes to the fore and become a pressing task of the present. Following this trend, this paper presents the author's model of estimating the state of the financial market. The comparative basis for this assessment was the integral indicator of the state, formed based on partial estimates of financial depth, access to finance, financial stability, and financial efficiency. The foundation for it was the methodology of fuzzy-set modeling, the purpose of which, regarding the issues under investigation, is in-depth study of the influence of financial structures on economic growth and the classification of financial indicators. Applying this model in practice, the authors have collected and analyzed extensive arrays of data concerning integral indicators of access to finance, financial depth, stability, and efficiency for two countries, Russia and the USA, and conducted a comparative analysis of the financial markets' changes during the selected period. The obtained results and observations allow to conclude that, unlike the USA, where instability and negative dynamics are observed, the financial market of Russia remains relatively stable during the period under review. Thus, on the basis of applying this model, it is possible to develop a more effective financial and banking policy. The model provides significant opportunities for deep and comprehensive analysis of financial phenomena and processes, which contributes to a more accurate assessment of the state of the financial market and rational forecasting of its future development.