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Xtreme Credit Risk Models: Implications For Bank Capital Buffers, David E. Allen, Akhmad R. Kramadibrata, Robert J. Powell, Abhay K. Singh

Research outputs 2011

The Global Financial Crisis (GFC) highlighted the importance of measuring and understanding extreme credit risk. This paper applies Conditional Value at Risk (CVaR) techniques, traditionally used in the insurance industry to measure risk beyond a predetermined threshold, to four credit models. For each of the models we use both Historical and Monte Carlo Simulation methodology to create CVaR measurements. The four extreme models are derived from modifications to the Merton structural model (which we term Xtreme-S), the CreditMetrics Transition model (Xtreme-T), Quantile regression (Xtreme-Q), and the author’s own unique iTransition model (Xtreme-i) which incorporates industry factors into transition matrices. For …