Construction of models of analysis and forecasting of the level of risks of the banking sector of the Republic of Belarus on the basis of integrated indicators

  • Valentin O. Suvalau National Bank of the Republic of Belarus, 20 Niezaliežnasci Avenue, Minsk 220008, Belarus
  • Katsiaryna A. Miniukovich Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus

Abstract

The process of constructing an econometric model for the purposes of creating an automated algorithm for forecasting the level of risks in the banking sector of the Republic of Belarus is being explored. The internal properties of the algorithm are based on the formalization of the process of constructing an econometric model with the fulfillment of the prerequisites, as well as machine learning.

Author Biographies

Valentin O. Suvalau, National Bank of the Republic of Belarus, 20 Niezaliežnasci Avenue, Minsk 220008, Belarus

specialist of the liquidity regulation department of the Financial Markets Operations Directorate

Katsiaryna A. Miniukovich, Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus

PhD (economics), docent; associate professor at the department of economic informatics, faculty of economics

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Published
2018-09-13
Keywords: model, forecasting, risks, econometric tools, integrated indicators, banking sector
Supporting Agencies The authors are very grateful to Petr A. Mamanovich, deputy Chairman of the Board, National Bank of the Republic of Belarus and Sergey N. Shevchuk, head of banking system risk analysis department of the Banking Supervision Main Directorate, National Bank of the Republic of Belarus.
How to Cite
Suvalau, V. O., & Miniukovich, K. A. (2018). Construction of models of analysis and forecasting of the level of risks of the banking sector of the Republic of Belarus on the basis of integrated indicators. Journal of the Belarusian State University. Economics, 1, 20-28. Retrieved from https://journals.bsu.by/index.php/economy/article/view/2234
Section
C. Mathematical and Quantitative Methods