Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/19751
Authors: 
Düllmann, Klaus
Year of Publication: 
2006
Series/Report no.: 
Discussion Paper, Series 2: Banking and Financial Supervision 2006,03
Abstract: 
Results from portfolio models for credit risk tell us that loan concentration in certain industry sectors can substantially increase the value-at-risk (VaR). The purpose of this paper is to analyze whether a tractable "infection model" can provide a meaningful estimate of the impact of concentration risk on the VaR. I apply rather parsimonious data requirements, which are comparable to those for Moody's Binomial Expansion Technique (BET) and considerably lower than for a multi-factor model. The infection model extends the BET model by introducing default infection into the hypothetical portfolio on which the real portfolio is mapped in order to obtain a simple solution for the VaR. The infection probability is calibrated for a range of typical values of input parameters, which capture the concentration of a portfolio in industry sectors, default dependencies between exposures and their credit quality. The accuracy of the new model is measured for test portfolios with a realistic industry-sector composition, obtained from the German central credit register. I find that a carefully calibrated infection model provides a reasonably close approximation to the VaR obtained from a multi-factor model and outperforms by far the BET model. The simulation results suggest that the calibrated infection model promises to provide a fit-for-purpose tool to measure concentration risk in business sectors that could be useful for risk managers and banking supervisors alike.
Subjects: 
asset correlation
concentration risk
credit risk
multi-factor model
value-at-risk
JEL: 
C20
C15
G21
Document Type: 
Working Paper

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