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Asset correlations and credit portfolio risk: an empirical analysis

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Author Info
Düllmann, Klaus
Scheicher, Martin
Schmieder, Christian

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Abstract

In credit risk modelling, the correlation of unobservable asset returns is a crucial component for the measurement of portfolio risk. In this paper, we estimate asset correlations from monthly time series of Moody’s KMV asset values for around 2,000 European firms from 1996 to 2004. We compare correlation and value-atrisk (VaR) estimates in a one–factor or market model and a multi-factor or sector model. Our main finding is a complex interaction of credit risk correlations and default probabilities affecting total credit portfolio risk. Differentiation between industry sectors when using the sector model instead of the market model has only a secondary effect on credit portfolio risk, at least for the underlying credit portfolio. Averaging firm-dependent asset correlations on a sector level can, however, cause a substantial underestimation of the VaR in a portfolio with heterogeneous borrower size. This result holds for the market as well as the sector model. Furthermore, the VaR of the IRB model is more stable over time than the VaR of the market model and the sector model, while its distance from the other two models fluctuates over time.

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Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 2: Banking and Financial Studies with number 2007,13.

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Date of creation: 2007
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Handle: RePEc:zbw:bubdp2:6352

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Related research
Keywords: Asset correlations sector concentration credit portfolio risk

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages

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  1. Nikola Tarashev & Haibin Zhu, 2008. "Specification and Calibration Errors in Measures of Portfolio Credit Risk: The Case of the ASRF Model," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 129-173, June. [Downloadable!]
  2. Schmidt, Rafael & Schmieder, Christian, 2007. "Modelling dynamic portfolio risk using risk drivers of elliptical processes," Discussion Paper Series 2: Banking and Financial Studies 2007,07, Deutsche Bundesbank, Research Centre. [Downloadable!]
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