прогнозирование

Introduction. Studying the relationship between macroeconomic indicators and the financial stability of companies is an important task for economic forecasting and risk management. This paper attempts to assess the nature of this relationship at an aggregated industry level, which helps to minimize errors associated with the non-representativeness of samples of individual enterprises. Еmpirical analysis. The research is based on an analysis of aggregated data from 2,230,121 Russian non-financial organizations for the period from 2014 to 2023.

Introduction. Data Mining algorithms enhancement leads to the solution of predictive analytics tasks in more efficient ways. The models ensembles are one of the actively developing areas, especially in those branches where predictive accuracy is more important than the interpretability of the model. Theoretical analysis. The forecasting problem requires careful study of the data set and methods suitable for analysis. It includes the solution of such subtasks as the choice of a forecasting model, the analysis of the forecast accuracy.

This paper is devoted to the uniform method of economic indicator’s approximation based at the P. L. Chebyshev’s investigations.