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  • 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. (xsd:string)
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?:dateModified
  • 2018 (xsd:gyear)
?:datePublished
  • 2018 (xsd:gyear)
?:doi
  • 10.3897/j.ruje.4.27737 ()
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  • true (xsd:boolean)
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  • en (xsd:string)
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?:issn
  • 2618-7213 ()
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  • 2 (xsd:string)
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?:name
  • Increase of banks' credit risks forecasting power by the usage of the set of alternative models (xsd:string)
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  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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  • GESIS-SSOAR (xsd:string)
  • In: Russian Journal of Economics, 4, 2018, 2, 155-174 (xsd:string)
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?:volumeNumber
  • 4 (xsd:string)