Subject. A region's economy growth is determined by the nature of a number of underlying economic processes, which include procedures for the financial market functions that play a crucial role. The function of financial institutions is most pronounced in the context of trends that are central to socio-economic development strategies. The article makes an attempt to systematize and highlight indicators, influencing and reflecting the essence of the economic category of finance, with an emphasis on social aspects. Objectives. The aim of the study is to review the economic category of finance in the context of indicators that have a significant impact on the nature of its function. Methods. I employ logical and systems approaches, methods of grouping, comparison, regression, and correlation analysis. The structured database of Rosstat official reporting served as information source. Results. The paper presents an economic-and-mathematical model of the financial market category. The model's functionality is sufficient to substantiate causal relationships between specific indicators. The proof was revealed empirically, based on the case of constituent entities of the Russian Federation that are part of the Siberian and the Volga Federal Districts, and using a dedicated software application. Conclusions. The developed theoretical, methodological and practical approaches, if used in practice, may help solve the problems of regional strategizing.
Keywords: macroeconomic indicator, regional economy, strategizing, development control, financial market
References:
Silin Ya.P., Animitsa E.G., Novikova N.V. [Theories of economic growth and economic cycles in the research of regional processes of new industrialization]. Journal of New Economy, 2019, vol. 20, no. 2, pp. 5–29. (In Russ.) URL: Link
Aganbegyan A.G. [Analysis and forecasting of socio-economic development of regions (methodical notes)]. Srednerusskii vestnik obshchestvennykh nauk = Central Russian Journal of Social Sciences, 2019, vol. 14, no. 4, pp. 15–28. (In Russ.) URL: Link
Glaz'ev S.Yu. [Priorities of the Russian economy's accelerated development during the transition to a new technological mode]. Ekonomicheskoe vozrozhdenie Rossii = Economic Revival of Russia, 2019, no. 2, pp. 12–16. URL: Link (In Russ.)
Medvedev D.A. [Russia-2024: The strategy of social and economic development]. Voprosy Ekonomiki, 2018, no. 10, pp. 5–28. (In Russ.) URL: Link
Balatskii E.V. [Global challenges of the fourth industrial revolution]. TERRA ECONOMICUS, 2019, vol. 17, no. 2, pp. 6–22. (In Russ.) URL: Link
Silin Ya.P., Animitsa E.G. [Contours of the digital economy in Russia]. Izvestiya Ural'skogo gosudarstvennogo ekonomicheskogo universiteta = Journal of Ural State University of Economics, 2018, vol. 19, no. 3, pp. 18–25. (In Russ.) URL: Link
Klistorin V.I. [Interlevel Financial Flows in the Budgetary System of the Russian Federation]. Region: Ekonomika i Sotsiologiya = Region: Economics and Sociology, 2018, no. 2, pp. 33–51. (In Russ.) URL: Link
Lebedeva N.A., Zhikharevich B.S. [Strategists about strategic planning]. Regional'naya ekonomika. Yug Rossii = Regional Economy. South of Russia, 2018, no. 1, pp. 6–15. (In Russ.) URL: Link
Mel'nikova L.V. [Theoretical arguments and empirical evidence in strategic planning]. Region: Ekonomika i Sotsiologiya = Region: Economics and Sociology, 2018, no. 2, pp. 52–80. (In Russ.) URL: Link
Okrepilov V.V., Makarov V.L., Bakhtizin A.R., Kuz'mina S.N. [Application of Supercomputer Technologies for Simulation of Socio-Economic Systems]. Ekonomika regiona = Economy of Region, 2015, no. 2, pp. 301–312. URL: Link (In Russ.)
Seliverstov V.E. [Strategic Planning and Strategic Miscounts: Russian Realia and Trends]. Region: Ekonomika i Sotsiologiya = Region: Economics and Sociology, 2016, no. 4, pp. 6–46. (In Russ.) URL: Link
Suslov N.I., Buzulutskov V.F. [Using the OMMM-TEK Information-Program-Model Complex in Scenario Analysis of the Development of the Fuel and Energy Sector in Regions: Methodical Aspects]. Region: Ekonomika i Sotsiologiya = Region: Economics and Sociology, 2017, no. 3, pp. 215–237. (In Russ.) URL: Link
Ghosh I., Jana R., Sanyal M. Analysis of Temporal Pattern, Causal Interaction and Predictive Modeling of Financial Markets Using Nonlinear Dynamics, Econometric Models and Machine Learning Algorithms. Applied Soft Computing, 2019, vol. 82. URL: Link
Lu Han. Correlation Predictive Modeling of Financial Markets. Procedia Computer Science, 2019, vol. 154, pp. 738–743. URL: Link
Edelev A.V., Zorkal'tsev V.I. [An Algorithm for Determining Optimal and Suboptimal Trajectories of the Development of a System]. Sibirskii zhurnal industrial'noi matematiki, 2019, vol. 22, no. 1, pp. 34–40. (In Russ.) URL: Link
Kuleshov V.V., Alekseev A.V., Yagol'nitser M.A. [Methods of Cognitive Analysis in Devising and Substantiating Strategies of Economic Development]. Problemy prognozirovaniya = Studies on Russian Economic Development, 2019, vol. 30, no. 2, pp. 185–191. URL: Link (In Russ.)
Kulapov M.N., Varfolomeev V.P., Karasev P.A. [Technological aspects of the control theory innovative processes: System analysis and approaches to modeling]. Drukerovskij Vestnik, 2018, no. 3, pp. 82–100. (In Russ.) URL: Link
Cook R.D., Weisberg S. Residuals and Influence in Regression. New York, Chapman and Hall, 1982, 230 p.
Rafindadi A., Mika'Ilu A. Sustainable Energy Consumption and Capital Formation: Empirical Evidence from the Developed Financial Market of the United Kingdom. Sustainable Energy Technologies and Assessments, 2019, vol. 35, pp. 265–277. URL: Link
Ivanitskii V.P., Tat'yannikov V.A. [Information Asymmetry in Financial Markets: Challenges and Threats]. Ekonomika regiona = Economy of Region, 2018, vol. 14, no. 4, pp. 1156–1167. URL: Link (In Russ.)
Dombret A., Foos D., Pliszka K., Schulz A. What Are the Real Effects of Financial Market Liquidity? Evidence on Bank Lending from the Euro Area. Journal of International Financial Markets, Institutions and Money, 2019, vol. 63, pp. 152–183. URL: Link
Xu Guo, Lianlian Song, Yun Fang, Lixing Zhu. Model Checking for General Linear Regression with Nonignorable Missing Response. Computational Statistics & Data Analysis, 2019, vol. 138, pp. 1–12. URL: Link 10.1016/j.csda.2019.03.009
Hanqin Shi, Liang Tao. Visual Comparison Based on Linear Regression Model and Linear Discriminant Analysis. Journal of Visual Communication and Image Representation, 2018, vol. 57, pp. 118–124. URL: Link