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The back side of banking in Russia: forecasting bank failures with negative capital

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  • Alexander Karminsky
  • Alexander Kostrov

Abstract

Since 2013, we have observed an increasing number of failed Russian banks with negative capital and falsified financial reporting. We use previously unavailable data for the period 2010-1H2015 to develop a logit model predicting the probability of bank failure with negative capital. In order to do so, we suggest solutions for the class imbalance and variable selection problems. The models chosen are confirmed to be robust and have longer forecasting horizons compared to previous research. Also, we implement a novel probability-based approach to the out-of-sample forecasting evaluation which confirms a good fit of the selected models to data. The model predicts bank failures in three quarters and finds 33% of actual failures among 5% of banks with the highest predicted probability to fail (out-of-sample). In addition, we make available previously unpublished banking data for Russia.

Suggested Citation

  • Alexander Karminsky & Alexander Kostrov, 2017. "The back side of banking in Russia: forecasting bank failures with negative capital," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(1/2), pages 170-209.
    • Handle: RePEc:ids:ijcome:v:7:y:2017:i:1/2:p:170-209
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    Citations

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    Cited by:

    1. D. Bidzhoyan S. & Д. Биджоян С., 2018. "Модель Оценки Вероятности Отзыва Лицензии У Российского Банка // Model For Assessing The Probability Of Revocation Of A License From The Russian Bank," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(2), pages 26-37.
    2. repec:zbw:bofitp:2019_006 is not listed on IDEAS
    3. Kostrov, Alexander & Mamonov, Mikhail, 2019. "The formation of hidden negative capital in banking: A product mismatch hypothesis," BOFIT Discussion Papers 6/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
    4. Alexander M. Karminsky & Ella Khromova, 2018. "Increase of banks’ credit risks forecasting power by the usage of the set of alternative models," Russian Journal of Economics, ARPHA Platform, vol. 4(2), pages 155-174, June.
    5. Kostrov, Alexander & Mamonov, Mikhail, 2019. "The formation of hidden negative capital in banking : A product mismatch hypothesis," BOFIT Discussion Papers 6/2019, Bank of Finland, Institute for Economies in Transition.
    6. Denis Shibitov & Mariam Mamedli, 2019. "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series wps43, Bank of Russia.
    7. Karminsky, A. & Rybalka, A., 2018. "Negative Net Worth of Manufacturing Companies: Corporate Governance and Industry Expectations," Journal of the New Economic Association, New Economic Association, vol. 38(2), pages 76-103.

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