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Increase of banks’ credit risks forecasting power by the usage of the set of alternative models

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  • Alexander M. Karminsky

    (National Research University Higher School of Economics, Moscow, Russia)

  • Ella Khromova

    (National Research University Higher School of Economics, Moscow, Russia)

Abstract

The paper is aimed at comparing the divergence of existing credit risk models and creating a synergic model with superior forecasting power based on a rating model and probability of default model of Russian banks. The paper demonstrates that rating models, if applied alone, tend to overestimate an instability of a bank, whereas probability of default models give underestimated results. As a result of the assigning of optimal weights and monotonic transformations to these models, the new synergic model of banks’ credit risks with higher forecasting power (predicted 44% of precise estimates) was obtained.

Suggested Citation

  • 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.
    • Handle: RePEc:arh:jrujec:v:4:y:2018:i:2:p:155-174
    DOI: 10.3897/j.ruje.4.27737
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    References listed on IDEAS

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    1. Esarey, Justin & Pierce, Andrew, 2012. "Assessing Fit Quality and Testing for Misspecification in Binary-Dependent Variable Models," Political Analysis, Cambridge University Press, vol. 20(4), pages 480-500.
    2. Christophe J. Godlewski, 2007. "Are Ratings Consistent with Default Probabilities?: Empirical Evidence on Banks in Emerging Market Economies," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(4), pages 5-23, August.
    3. D Rösch & H Scheule, 2014. "Forecasting probabilities of default and loss rates given default in the presence of selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 393-407, March.
    4. Alessandro Santoni & Barbara Arbia, 2013. "Assessing Rating Agencies' Ability to Predict Bank Bankruptcy – The Lace Financial Case," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(2), pages 203-215, July.
    5. Pompella, Maurizio & Dicanio, Antonio, 2017. "Ratings based Inference and Credit Risk: Detecting likely-to-fail Banks with the PC-Mahalanobis Method," Economic Modelling, Elsevier, vol. 67(C), pages 34-44.
    6. Karminsky, Alexandr & Peresetsky, Anatoly, 2007. "Models of Banks Ratings," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 5(1), pages 3-19.
    7. Bokov, Vassily & Vernikov, Andrei, 2008. "Quality of governance and bank valuation in Russia: An empirical study," MPRA Paper 11990, University Library of Munich, Germany.
    8. Raquel Florez-Lopez & Juan Manuel Ramon-Jeronimo, 2014. "Modelling credit risk with scarce default data: on the suitability of cooperative bootstrapped strategies for small low-default portfolios," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 416-434, March.
    9. 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.
    10. Karminsky, A. & Morgunov, A. & Bogdanov, P., 2015. "The Assessment of Default Probability for the Project Finance Transactions," Journal of the New Economic Association, New Economic Association, vol. 26(2), pages 99-122.
    11. Donald P. Morgan, 2002. "Rating Banks: Risk and Uncertainty in an Opaque Industry," American Economic Review, American Economic Association, vol. 92(4), pages 874-888, September.
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    More about this item

    Keywords

    banks; credit ratings; probability of default; ordered logit models; ordered probit models; rating agencies;
    All these keywords.

    JEL classification:

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

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