Forecasting loss given default of bank loans with multi-stage model

Yuta Tanoue*, Akihiro Kawada, Satoshi Yamashita

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


Probability of default (PD) and loss given default (LGD) are key risk parameters in credit risk management. The majority of LGD research is based on the corporate bond market and few studies focus on the LGD of bank loans even in Japan because of the lack of available public data on bank loan losses. Consequently, knowledge concerning Japanese bank loan LGD is scarce. This study uses Japanese bank loan data to analyze the influencing factors of LGD and to develop a (multi-stage) model to predict LGD and expected loss (EL). We found that collateral, guarantees, and loan size impact LGD. Further, we confirmed that our multi-stage LGD model has superior predictive accuracy than the corresponding OLS model, Tobit model and Inflated beta regression model.

Original languageEnglish
Pages (from-to)513-522
Number of pages10
JournalInternational Journal of Forecasting
Issue number2
Publication statusPublished - 2017 Apr 1
Externally publishedYes


  • Credit risk modeling
  • Expected loss
  • Loss given default
  • Multi-stage model
  • Probability of default

ASJC Scopus subject areas

  • Business and International Management


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