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Determinants of risk, profitability and default probability of Russian banks

Author

Listed:
  • Bekirova, Olga

    (Russian Presidential Academy of National Economy and Public Administration, Moscow, Russian Federation)

  • Zubarev, Andrey

    (Russian Presidential Academy of National Economy and Public Administration, Moscow, Russian Federation)

Abstract

In this paper, based on quarterly data on the financial statements of Russian banks for the period from mid-2013 to the end of 2021, using econometric methods of analysis, we estimated the factors that affect both the probability of bank default as well as other indicators of its activity — risk and profitability. The results obtained showed that balance sheet ratios are significantly correlated with the probability of bank default, its risk of insolvency, and profitability. Asset quality, a bank’s size, a capital ratio, and liquidity creation are important determinants of these bank’s characteristics. The insolvency risk (measured as a Z-score), in turn, is significantly negatively correlated with the probability of default and profitability (ROA).

Suggested Citation

  • Bekirova, Olga & Zubarev, Andrey, 2023. "Determinants of risk, profitability and default probability of Russian banks," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 71, pages 20-38.
    • Handle: RePEc:ris:apltrx:0476
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    References listed on IDEAS

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    1. Mikhail Mamonov, 2020. "Maturity Structure of Banking Transactions and Its Role in Predicting Negative Net Worth of Banks," Russian Journal of Money and Finance, Bank of Russia, vol. 79(2), pages 70-100, June.
    2. Forgione, Antonio Fabio & Migliardo, Carlo, 2018. "Forecasting distress in cooperative banks: The role of asset quality," International Journal of Forecasting, Elsevier, vol. 34(4), pages 678-695.
    3. Allen N. Berger & Christa H. S. Bouwman, 2009. "Bank Liquidity Creation," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3779-3837, September.
    4. M. E. Mamonov., 2018. "Hidden "holes" in the capital of banks and the supply of credit to the real sector of economy," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 5.
    5. Betz, Frank & Oprică, Silviu & Peltonen, Tuomas A. & Sarlin, Peter, 2014. "Predicting distress in European banks," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 225-241.
    6. Peresetsky, Anatoly, 2013. "Modeling reasons for Russian bank license withdrawal: Unaccounted factors," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 30(2), pages 49-64.
    7. Rebel Cole & Lawrence White, 2012. "Déjà Vu All Over Again: The Causes of U.S. Commercial Bank Failures This Time Around," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 5-29, October.
    8. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
    9. Zubarev, Andrey (Зубарев, Андрей) & Bekirova, Olga (Бекирова, Ольга), 2020. "Analysis of Bank Default Factors in 2013–2019 [Анализ Факторов Банковских Дефолтов 2013–2019 Годов]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, pages 106-133, June.
    10. Fungacova, Zuzana & Turk, Rima & Weill, Laurent, 2021. "High liquidity creation and bank failures," Journal of Financial Stability, Elsevier, vol. 57(C).
    11. Zheng, Chen & (Wai Kong) Cheung, Adrian & Cronje, Tom, 2019. "The moderating role of capital on the relationship between bank liquidity creation and failure risk," Journal of Banking & Finance, Elsevier, vol. 108(C).
    12. Antunes, António & Bonfim, Diana & Monteiro, Nuno & Rodrigues, Paulo M.M., 2018. "Forecasting banking crises with dynamic panel probit models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 249-275.
    13. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    14. Lev Fomin, 2019. "Do Higher Interest Rates on Loans and Deposits and Advertising Spending Cuts Forecast Bank Failures? Evidence from Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 78(2), pages 94-112, June.
    15. Hwang, Dar-Yeh & Lee, Cheng F. & Liaw, K. Thomas, 1997. "Forecasting bank failures and deposit insurance premium," International Review of Economics & Finance, Elsevier, vol. 6(3), pages 317-334.
    16. Zubarev, Andrei, 2012. "The Factors of Stability of Russian Banks during the Crisis of 2008—2009," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, pages 126-142, August.
    17. Andrey Zubarev & Kirill Shilov, 2022. "Bank Default's Factors Differentiation Based on License Withdrawal Reasons," HSE Economic Journal, National Research University Higher School of Economics, vol. 26(1), pages 69-103.
    18. Caggiano, Giovanni & Calice, Pietro & Leonida, Leone, 2014. "Early warning systems and systemic banking crises in low income countries: A multinomial logit approach," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 258-269.
    19. Karminsky, A. & Kostrov, A., 2013. "Modeling the Default Probabilities of Russian Banks: Extended Abillities," Journal of the New Economic Association, New Economic Association, vol. 17(1), pages 64-86.
    20. M. E. Mamonov, 2018. "Hidden “holes” in the capital of banks and the supply of credit to the real sector of economy," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 5.
    21. Assaf, A. George & Berger, Allen N. & Roman, Raluca A. & Tsionas, Mike G., 2019. "Does efficiency help banks survive and thrive during financial crises?," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 445-470.
    22. Belousova, V. & Kozyr, I., 2016. "How Do Macroeconomic Indicators Influence Banking Profitability in Russia?," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 77-103.
    23. DeYoung, Robert & Torna, Gökhan, 2013. "Nontraditional banking activities and bank failures during the financial crisis," Journal of Financial Intermediation, Elsevier, vol. 22(3), pages 397-421.
    24. Elekdag, Selim & Malik, Sheheryar & Mitra, Srobona, 2020. "Breaking the Bank? A Probabilistic Assessment of Euro Area Bank Profitability," Journal of Banking & Finance, Elsevier, vol. 120(C).
    25. Shim, Jeungbo, 2019. "Loan portfolio diversification, market structure and bank stability," Journal of Banking & Finance, Elsevier, vol. 104(C), pages 103-115.
    26. Zhivaikina, A. & Peresetsky, A., 2017. "Russian Bank Credit Ratings and Bank License Withdrawal 2012-2016," Journal of the New Economic Association, New Economic Association, vol. 36(4), pages 49-80.
    27. Asli Demirgüç-Kunt & Enrica Detragiache, 1998. "The Determinants of Banking Crises in Developing and Developed Countries," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 81-109, March.
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    More about this item

    Keywords

    banking sector; banking license revocation; default; insolvency risk; Z-score; return on assets; return on capital; liquidity creation; Bank of Russia;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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