Modeling Scenarios and Forecasting Risks of Bankruptcy for Metallurgical Enterprises: The Case of the Sverdlovsk Region

Ilya V. Naumov (), Natalia L. Nikulina () and Anna A. Bychkova ()
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Ilya V. Naumov: Institute of Economics UB RAS, Yekaterinburg, Russian Federation
Natalia L. Nikulina: Institute of Economics UB RAS, Yekaterinburg, Russian Federation
Anna A. Bychkova: Institute of Economics UB RAS, Yekaterinburg, Russian Federation

Finansovyj žhurnal — Financial Journal, 2025, issue 4, 119-136

Abstract: The subject of the study is forecasting of the probability of bankruptcy of enterprises in the metallurgical industry. Particular attention is paid to assessing the impact of macroeconomic factors, such as currency exchange rate dynamics, investments in fixed capital, the degree of depreciation of fixed assets and asset turnover, on the financial stability of enterprises in the industry. The objective of the work is to develop scenario models for predicting the probability of bankruptcy of metallurgical enterprises in the Sverdlovsk Region using control variables characterizing the influence of economic factors. The authors used regression analysis and autoregressive modeling (ARIMA/ARMA). Inertial, extremely pessimistic and optimistic forecasts were constructed for changes in key factors affecting the stability of enterprises in the metallurgical sector (from the level of depreciation of fixed assets, the volume of investments in fixed capital, the production technologies used, the growth of foreign currency exchange rates, etc.), as well as corresponding forecast scenarios for the probability of their bankruptcy. Forecasting the probability of bankruptcy among metallurgical enterprises in the Sverdlovsk Region shows that large enterprises have moderate financial stability, while small and medium-sized enterprises are exposed to significant risks. The scenario analysis revealed the key role of technological renewal and investment in fixed assets as factors that increase the stability of enterprises. The methodological approach proposed in the paper allows to determine the financial stability of enterprises, assess the probability of their bankruptcy and the impact of the key factors using a regression model, forecast the dynamics of these factors using autoregressive modeling with a moving average, and design forecast scenarios. This approach can be applied in strategic planning and development of state support measures for enterprises aimed at reducing bankruptcy risks and ensuring sustainable development of the industry.

Keywords: probability of bankruptcy; regression analysis; ARIMA modeling; metallurgy; forecast; region (search for similar items in EconPapers)
JEL-codes: G33 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:fru:finjrn:250407:p:119-136

DOI: 10.31107/2075-1990-2025-4-119-136

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