Research of default risk level of Russian energy

Бесплатный доступ

The liberalization of the electricity market intensifies the competition for investors in the Russian energy market, for which the financial stability of energy companies is an important criterion. The paper presents the mathematical modelling of integrated assessment of the default risk level of Russian energy companies, taking into account their specific characteristics: type of the energy business, form of ownership, and regional specific. The research is based on the industry approach to the diagnostics of default risk level of energy companies. The approach includes the logit-model and assessment of the coefficients significance. The complexity of this model is conditioned by the study of external and internal financial and economic indicators, as well as qualitative criteria based on the introduction of dummy-variables. Four groups of default risk level of Russian energy companies are proposed. The use of mathematical modelling tools increases the accuracy of assessing the financial insolvency of energy companies in comparison with the traditional methods. Therefore, the proposed approach is novel, relevant, and practically significant. Research veracity is confirmed by the practical implementation. We recommend the use of the proposed methodology in assessment of the current state and development strategy of Russian energy companies, as well as by investors and analysts to make financial decisions.

Еще

Energy, energy business, default, probability of default, investments, risk, logit-model, modelling, logit-модель

Короткий адрес: https://sciup.org/147232940

IDR: 147232940   |   DOI: 10.14529/mmp190215

Список литературы Research of default risk level of Russian energy

  • Mokhov, V.G. Modelling of Green Investments Risks / V.G. Mokhov, G.S. Chebotareva, P.M. Khomenko // Вестник ЮУрГУ. Серия: Математическое моделирование и программирование. - 2018. - T. 11, № 2. - С. 154-159.
  • Sorland, B.F. What Drives Financial Distress Risk and Default Rates of Leveraged Buyout Targets? / B.F. Sorlnd, M.N. Rudel // Empirical Evidence from European Transactions, Norwegian School of Economics, 2015.
  • Varotto, S.E. Modelling Decisions of Control Transi-Tions and Target Speed Regulations in Full-Range Adaptive Cruise Control Based on Risk Allostasis / S.E. Varotto, E. Silvia, H. Farah, T. Toledo // Theory Transportation Research Part B-Methodological. - 2018. - V. 117. - P. 318-341.
  • Minal, S. Development of Neuro-Fuzzy-Based Multimodal Mode Choice Model for Commuter in Delhi / S. Minal, C.R. Sekhar, E. Madhu // Intelligent Transport Systems. - 2019. - V. 13, № 2. - P. 293-251.
  • Хайдаршина, Г.А. Комплексная модель оценки риска банкротства / Г.А. Хайдаршина // Финансы. - 2009. - № 2. - С. 67-69.
Краткое сообщение