STATISTICAL ANALYTICS OF FINANCIAL STABILITY OF ENTERPRISES: METHODS OF ASSESSMENT AND FORECASTING
Abstract
The purpose of the article is to identify modern methods of statistical analytics for assessing and forecasting the financial stability of enterprises, as well as to justify their application in conditions of market instability. The study uses a comprehensive approach to statistical analytics of the financial stability of enterprises. The methods of correlation-regression analysis are considered to determine the relationships between financial indicators, as well as cluster analysis for grouping enterprises by the level of stability. Time series methods are evaluated to predict changes in financial condition. Content analysis is carried out on the basis of official statistical data and the processing of literary sources on the topic of the study. The results obtained are interpreted based on the method of logical generalization taking into account macroeconomic factors. The article considers the main aspects of statistical analytics of financial stability of enterprises and its significance for assessing and forecasting their development. Key approaches to the analysis of financial stability based on the use of statistical methods of processing and interpreting financial data are identified. The impact of liquidity, profitability, autonomy and financial leverage on the overall stability of enterprises is analyzed. The features of the application of correlation-regression analysis, factor analysis and clustering methods to determine the level of financial stability and identify patterns in the financial activities of enterprises are clarified. The possibilities of forecasting changes in financial condition using statistical time series models and neural networks are investigated. The advantages of statistical analytics compared to traditional methods of financial analysis are identified, which allows ensuring the objectivity of assessment and accuracy of forecasting. Factors affecting the financial stability of enterprises are investigated, in particular the level of asset diversification, capital structure and macroeconomic conditions. Mechanisms for minimizing financial risks are identified through the application of statistical methods of sensitivity analysis and scenario modeling.
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