CVaR and Credit Risk Measurement

Document Type

Conference Proceeding


International Association for Mathematics and Computers in Simulation


Business and Law


Accounting, Finance and Economics




This article was originally published as: Powell, R. J. , & Allen, D. E. (2009). CVaR and Credit Risk Measurement. Proceedings of MODSIM09. (pp. 1508-1514). Cairns. International Association for Mathematics and Computers in Simulation. Original article available here


The link between credit risk and the current financial crisis accentuates the importance of measuring and predicting extreme credit risk. Conditional Value at Risk (CVaR) is a method used widely in the insurance industry to measure extreme risk, and has also gained popularity as a measure of extreme market risk. We combine the CVaR market approach with the Merton / KMV credit model to generate a model measuring credit risk under extreme market conditions. The Merton / KMV model is a popular model used by Banks to predict probability of default (PD) of customers based on movements in the market value of assets. The model uses option pricing methodology to estimate distance to default (DD) based on movements in the market value of assets. This model has been popularized among Banks for measuring credit risk by KMV who use the DD approach of Merton but apply their extensive default data base to modify PD outcomes. Our extreme credit model is used to compare default risk among sectors in an Australian setting. An in depth understanding of sectoral risk is vital to Banks to ensure that there is not an overconcentration of credit risk in any sector. This paper demonstrates how CVaR methodology can be applied to credit risk in different economic circumstances and provides Australian Banks with important insights into extreme sectoral credit risk leading up to and during the financial crisis. It is precisely at times of extreme risk that companies are most likely to default. This paper provides an understanding of which industries are at most risk during these extreme circumstances. The paper shows a significant increase in default probabilities across all industries during the current financial crisis. Industries with low equity are most affected. The increase is most prominent in the Real Estate, Financial and Mining industries. Industries which have best weathered the storm include Food, Beverage & Tobacco, Pharmaceuticals & Biotechnology and Technology. Both prior to and during the financial crisis, significant correlation is found between those industries that are risky from a market (share price) perspective and those industries that are risky from a credit perspective. There is significant movement in sector risk rankings since the onset of the financial crisis, meaning that those industries that were most risky prior to the financial crisis are not the same industries that are most risky during the financial crisis.