Eurasian Economic Review

, Volume 4, Issue 1, pp 81–98 | Cite as

The probability of default in Russian banking

  • Alexander M. KarminskyEmail author
  • Alexander Kostrov
Original Paper


We compare several models for estimating the default probabilities of Russian banks using national statistics from 1998 to 2011, and find that a binary logit regression with a quasi-panel data structure works best. The results indicate that there is a quadratic U-shaped relationship between a bank’s capital adequacy ratio and its probability of default. In addition, macroeconomic, institutional, and time factors significantly improve model accuracy. These results are useful for national financial regulatory authorities, as well as for risk-managers in commercial banks.


Probability of default Banks Risk-management Default classification 

JEL Classification

G21 G24 G32 



The work is partially supported by the International Laboratory of Quantitative Finance, NRU HSE, RF government Grant, ag. 14.A12.31.0007; a Research project No. 05-0030 ≪Analysis of credit institutions insolvency≫, NRU HSE, RF.


  1. Anzoategui, D., Peria, M., & Melecky, M. (2012). Bank competition in Russia: An examination at different levels of aggregation. Emerging Markets Review, 13(1), 52–53.CrossRefGoogle Scholar
  2. Bluhm, C., Overbeck, L., & Wagner, C. (2010). Introduction to credit risk modeling. London: Chapman and Hall/CRC.Google Scholar
  3. Bock, R., & Demyanets, A. (2012). Bank asset quality in emerging markets: Determinants and spillovers. IMF Working Papers, 12/71.Google Scholar
  4. Chernykh, L., & Theodossiou, A. (2011). Determinants of bank long-term lending behavior: Evidence from Russia. Multinational Finance Journal, 15(3/4), 193–216.CrossRefGoogle Scholar
  5. Claeys, S., & Schoors, K. (2007). Bank supervision Russian style: Evidence of conflicts between micro- and macro-prudential concerns. Journal of Comparative Economics, 35(3), 630–657.CrossRefGoogle Scholar
  6. Clarke, G., Cull, R., & Shirley, M. (2005). Bank privatization in developing countries: A summary of lessons and findings. Journal of Banking & Finance, 29(8/9), 1905–1930.CrossRefGoogle Scholar
  7. Fungacova, Z., & Solanko, L. (2009). Risk-taking by Russian banks: Do location, ownership and size matter? BOFIT Discussion Papers, 21/2008.Google Scholar
  8. Fungacova, Z., & Weill, L. (2009). How market power influences bank failures: Evidence from Russia. BOFIT Discussion Papers, 12/2009.Google Scholar
  9. Greene, W. (2007). Econometric analysis (6th ed.). New Jersey: Prentice Hall.Google Scholar
  10. Hainsworth, R., Karminsky, A., & Solodkov, V. (2013). Arm’s length method for comparing rating scales. Eurasian Economic Review, 3(2), 114–135.Google Scholar
  11. Hanafi, M., Santi, F., & Muazaroh, (2013). The impact of ownership concentration, commissioners on bank risk and profitability: Evidence from Indonesia. Eurasian Economic Review, 3(2), 183–202.CrossRefGoogle Scholar
  12. He, H., & Edwardo, A. (2009). Learning from imbalanced data. IEEE Transactions on Knowledge and Data Engineering, 21(9), 1263–1284.CrossRefGoogle Scholar
  13. Hosmer, D., & Lemeshow, S. (2000). Applied logistic regression. New York: Wiley.CrossRefGoogle Scholar
  14. Karminsky, A. (2010). Повышение устойчивости и эффективности банковской системы [Improving stability and efficiency of the Russian banking system], in V. Polterovich Стратегия модернизации российской экономики [Modernization strategy for Russian economy], Saint Petersburg, Aletheia.Google Scholar
  15. Karminsky, A., Peresetsky, A., & Petrov, A. (2005). Рейтинги в экономике: методология и практика [Ratings in economics: Methodology and practice]. Moscow: Finansi i Statistika.Google Scholar
  16. Lanine, G., & Vennet, R. (2006). Failure prediction in the Russian bank sector with logit and trait recognition models. Expert Systems with Applications, 30(3), 463–478.CrossRefGoogle Scholar
  17. Mannasoo, K., & Mayes, D. (2009). Explaining bank distress in Eastern European transition economies. Journal of Banking & Finance, 33(2), 244–253.CrossRefGoogle Scholar
  18. Micco, A., Panizza, U., & Yanez, M. (2007). Bank ownership and performance. Does politics matter? Journal of Banking & Finance, 31(1), 219–241.CrossRefGoogle Scholar
  19. Peresetsky, А. (2010). Модели причин отзыва лицензий российских банков [Modeling license revocations of Russian banks]/Preprint #WP/2010/085. New Economic School.Google Scholar
  20. Peresetsky, A., Karminsky, A., & Golovan, S. (2011). Probability of default models of Russian banks. Economic Change and Restructuring, 44(4), 297–334.CrossRefGoogle Scholar
  21. Tabak, B., Craveiro, G., and Cajueiro, D. (2011). Bank efficiency and default in Brazil: Causality tests. The Central Bank of Brazil Working Paper Series, 253.Google Scholar
  22. Totmyanina, K. (2011). Обзор моделей вероятности дефолта [Review of probability of default models]. Journal of Financial Risk Management, 1(25), 3–17.Google Scholar
  23. Vernikov, A. (2011). Government banking in Russia: Magnitude and new features. IWH Discussion Papers, 13.Google Scholar
  24. Yigit, I., & Behram, N. (2013). The relationship between diversification strategy and organizational performance in developed and emerging economy. Eurasian Business Review, 3(2), 121–136.CrossRefGoogle Scholar

Copyright information

© Eurasia Business and Economics Society 2014

Authors and Affiliations

  1. 1.International Laboratory of Quantitative Finance, Higher School of EconomicsMoscowRussia

Personalised recommendations