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ИД «Финансы и кредит»






Finance and Credit

Developing the stress testing algorithms for companies: A metal industry case study

Vol. 29, Iss. 10, OCTOBER 2023

Received: 20 July 2020

Received in revised form: 30 July 2020

Accepted: 11 August 2020

Available online: 30 October 2023

Subject Heading: BUSINESS VALUE

JEL Classification: L10

Pages: 2376–2408


Vera G. KOGDENKO National Research Nuclear University MEPhI, Moscow, Russian Federation


Subject. The article addresses the development of stress testing algorithms for companies operating in the real economy.
Objectives. The study generalizes stress-testing algorithms and assesses the hypothesis about the resistance of steel companies to external shocks.
Methods. I employ general scientific principles and methods of research, like abstraction, generalization of approaches of domestic and foreign authors to stress testing and industry analysis.
Results. I developed methods of aggregated direct single-factor historical stress testing based on the top-down approach. The methodology includes three stages. First, I identify stress-testing parameters: stress factors, variables and constant model parameters. Revenue, which is influenced by market risk, is defined as a stress factor. At the second stage, I substantiate the algorithms for predicting stress-testing parameters, then I calculate the predictive values of variable and permanent parameters of the model, assess the volatility of the stress factor, calculate confidence intervals and justify stress-testing scenarios. At the final stage, the results of stress testing are analyzed. The methodology was tested on the investigation of data of 454 metallurgical enterprises.
Conclusions. The companies assigned to the first group (20% of companies that account for 80% of revenue) have a high degree of resilience in the short term, owing to their operational efficiency, which ensures continuity of operations. In the long term, iron and steel companies have insufficient resilience due to the high loan debt burden offsetting the aggressive dividend policy, and inadequate investment in production capacity and safety.

Keywords: risk assessment, stress testing, metallurgy


  1. Danilova E.O., Markov K.V. [Macroprudential stress-testing of the financial sector: International experience and the Bank of Russia's approaches]. Den'gi i kredit = Russian Journal of Money and Finance, 2017, no. 10, pp. 3–15. URL: Link (In Russ.)
  2. Vershinina O.V., Labusheva Ya.G., Sultaniev I.S. [The role of stress testing in risk management of insurance company]. Biznes. Obrazovanie. Pravo = Business. Education. Law, 2019, no. 1, pp. 132–136. URL: Link (In Russ.)
  3. Dyundik K.A., Kokhno P.A. [Features of management of the integrated industry companies]. Nauchnyi vestnik oboronno-promyshlennogo kompleksa Rossii = Scientific Bulletin of the Military-Industrial Complex of Russia, 2017, no. 3, pp. 30–50. URL: Link (In Russ.)
  4. Malkina M.Yu., Ovcharov A.O. [Financial Stress Index as a Generalized Indicator of Financial Instability]. Nauchno-issledovatel'skii finansovyi institut. Finansovyi zhurnal = Financial Research Institute. Financial Journal, 2019, no. 3, pp. 38–54. (In Russ.) URL: Link
  5. Korshikova M.V. [Diversification in the management of economic risks: The analytic hierarchy process]. Vestnik APK Stavropol'ya = Agricultural Bulletin of Stavropol Region, 2015, no. 2, pp. 259–263. URL: Link (In Russ.)
  6. Grigoryan A.A. [Stress-testing use at forecasting of financial stability of the organization]. Mezhdunarodnyi bukhgalterskii uchet = International Accounting, 2011, no. 6, pp. 45–49. URL: Link (In Russ.)
  7. Lyadova Yu.O. [Analysis of factors affecting the financial stability of the enterprise, and methods of their evaluation]. Izvestiya Sankt-Peterburgskogo gosudarstvennogo ekonomicheskogo universiteta, 2018, no. 4, pp. 175–179. URL: Link (In Russ.)
  8. Beaver W.H. Financial Ratio as Predictors of Failure. Journal of Accounting Research, 1966, no. 4, pp. 71–111. URL: Link
  9. Altman E.I. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 1968, vol. 23, no. 4, pp. 589–609. URL: Link
  10. Lyubushin N.P., Babicheva N.E., Lylov A.I. [Economic analysis of business entities' sustainable development under cyclicality]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2018, vol. 17, iss. 1, pp. 4–17. (In Russ.) URL: Link
  11. Konovalova K.Yu. [Questions of modern theoretical aspects of the control system of risks in commercial bank]. Nauchnye izvestiya = Scientific News, 2017, no. 7, pp. 27–36. URL: Link (In Russ.)
  12. Selyutin V.V., Vlasenko E.A., Mesropyan K.E. [Model approaches to stress testing of banks and banking system: Modern trends and opportunities for improvement]. Finansy i kredit = Finance and Credit, 2017, vol. 23, iss. 8, pp. 430–449. (In Russ.) URL: Link
  13. Popova K.A. [Stress-testing instruments and their practical use]. Khronoekonomika, 2019, no. 5. (In Russ.) URL: Link
  14. Kogdenko V.G. [Improving the methodology for industry analysis based on the Harvard paradigm]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2019, vol. 18, iss. 10, pp. 1847–1880. (In Russ.) URL: Link
  15. Kazakova N.A., Kogdenko V.G., Kuz'mina-Merlino I., Sivkova A.E. [Assessment and forecasting of economic sustainability of Russian metallurgical companies]. Chernye Metally, 2020, no. 4, pp. 56–64. URL: Link (In Russ.)
  16. Neingo P.N., Tholana T. Trends in Productivity in the South African Gold Mining Industry. Journal of the Southern African Institute of Mining and Metallurgy, 2016, vol. 116, iss. 3, pp. 283–290. URL: Link
  17. Yong He, Nuo Liao, Jiwen Rao et al. The Optimization of Investment Strategy for Resource Utilization and Energy Conservation in Iron Mines Based on Monte Carlo and Intelligent Computation. Journal of Cleaner Production, 2019, vol. 232, pp. 672–691. URL: Link
  18. Christmann P. Towards a More Equitable Use of Mineral Resources. Natural Resources Research, 2018, vol. 27, iss. 2, pp. 159–177. URL: Link
  19. Kijewska A. Conditions for Sustainable Growth (SGR) for Companies from Metallurgy and Mining Sector in Poland. Metalurgija, 2016, vol. 55, iss. 1, pp. 139–142. URL: Link
  20. Asr E., Kakaie R., Ataei M. et al. A Review of Studies on Sustainable Development in Mining Life Cycle. Journal of Cleaner Production, 2019, vol. 229, pp. 213–231. URL: Link
  21. Lyubushin N.P., Babicheva N.E., Igoshev A.K., Kondrashova N.V. [Modeling the sustainable development of different hierarchical level economic systems based on a resource-oriented approach]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2015, no. 48, pp. 2–12. URL: Link (In Russ.)
  22. Endovitskii D.A., Babicheva N.E., Lyubushin N.P. [Using a Resource-Oriented Approach to Assess the Economy's System-Wide Balance]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2018, vol. 17, iss. 12, pp. 1298–1309. (In Russ.) URL: Link
  23. Sigel' E. Proschitat' budushchee: Kto kliknet, kupit, sovret ili umret [Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die]. Moscow, Al'pina Pablisher Publ., 2018, 374 p.

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