Take it to the limit: Innovative CVaR applications to extreme credit risk measurement

D. E. Allen, R. J. Powell, A. K. Singh

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The Global Financial Crisis (GFC) demonstrated the devastating impact of extreme credit risk on global economic stability. We develop four credit models to better measure credit risk in extreme economic circumstances, by applying innovative Conditional Value at Risk (CVaR) techniques to structural models (called Xtreme-S), transition models (Xtreme-T), quantile regression models (Xtreme-Q), and the author's unique iTransition model (Xtreme-i) which incorporates industry factors into transition matrices. We find the Xtreme-S and Xtreme-Q models to be the most responsive to changing market conditions. The paper also demonstrates how the models can be used to determine capital buffers required to deal with extreme credit risk.

LanguageEnglish
Pages465-475
Number of pages11
JournalEuropean Journal of Operational Research
Volume249
Issue number2
DOIs
Publication statusPublished - 1 Mar 2016
Externally publishedYes

Fingerprint

Conditional Value at Risk
Credit Risk
Extremes
Quantile Regression
Regression Model
Economics
Financial Crisis
Transition Model
Transition Matrix
Structural Model
Model
Buffer
Industry
Credit risk
Conditional value at risk
Risk measurement
Demonstrate
Regression model
Quantile regression

Keywords

  • Capital buffers
  • Conditional probability of default
  • Conditional Value at Risk
  • Credit risk
  • Uncertainty modeling

Cite this

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abstract = "The Global Financial Crisis (GFC) demonstrated the devastating impact of extreme credit risk on global economic stability. We develop four credit models to better measure credit risk in extreme economic circumstances, by applying innovative Conditional Value at Risk (CVaR) techniques to structural models (called Xtreme-S), transition models (Xtreme-T), quantile regression models (Xtreme-Q), and the author's unique iTransition model (Xtreme-i) which incorporates industry factors into transition matrices. We find the Xtreme-S and Xtreme-Q models to be the most responsive to changing market conditions. The paper also demonstrates how the models can be used to determine capital buffers required to deal with extreme credit risk.",
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Take it to the limit : Innovative CVaR applications to extreme credit risk measurement. / Allen, D. E.; Powell, R. J.; Singh, A. K.

In: European Journal of Operational Research, Vol. 249, No. 2, 01.03.2016, p. 465-475.

Research output: Contribution to journalArticleResearchpeer-review

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