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

Alexandr Karminsky and Ella Khromova ()
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Ella Khromova: National Research University Higher School of Economics, Moscow, Russia

Russian Journal of Economics, 2018, vol. 4, issue 2, 155-174

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.

Keywords: banks; credit ratings; probability of default; ordered logit models; ordered probit models; rating agencies (search for similar items in EconPapers)
JEL-codes: G21 G33 (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:arh:jrujec:v:4:y:2018:i:2:p:155-174

DOI: 10.3897/j.ruje.4.27737

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