APPLICATION OF STOCHASTIC REGRESSION ANALYSIS MODELS IN THE PROCESS OF FORECASTING LIQUIDITY AND PROFI

Abstract

The sanctions imposed on Russian companies are reducing the opportunity to increase exports to foreign, primarily European, markets. Limited access to modern imported equipment hinders the upgrade of production capacity, scheduled maintenance, and maintaining the global competitiveness of their products. Financial market volatility complicates long-term financial planning and budgeting. Rising inflation is leading to a tightening of monetary policy and, consequently, an increase in the cost of borrowing. In such conditions, the key factor in preserving a business is maintaining a sufficient level of liquidity, which is ensured by balancing operating, investment, and financial cash flows, regardless of external conditions. Within the framework of this study, an empirical base was formed based on the data of accounting (financial) statements of systemically important enterprises of the Russian oil and gas industry. The use of correlation analysis and multivariate regression methods allowed us to identify indicators associated with increased liquidity and profitability of domestic oil and gas companies. Also, as part of the current work, an analysis was conducted of the impact of external factors on profitability, such as GDP, mineral extraction tax, the ratio of exports and imports, and others.