Forecasting credit event frequency – empirical evidence for West German firms

Alfred Hamerle, Thilo Liebig and Harald Scheule
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Alfred Hamerle: Department of Statistics, Faculty of Business Management, Economics and Management Information Systems, University of Regensburg
Thilo Liebig: Deutsche Bundesbank

Published Paper Series from Finance Discipline Group, UTS Business School, University of Technology, Sydney

Abstract: The main challenge of forecasting credit default risk in loan portfolios may be seen in forecasting the default probabilities and the default correlations. We derive a Merton-style threshold value model for the default probability which treats the asset value of a firm as unknown and uses a factor model instead. In addition, we demonstrate how default correlations can be easily modeled. The empirical analysis is based on a large data set of German firms provided by Deutsche Bundesbank. We find that default probabilities can be forecast given the values of risk drivers known at the point of time at which the forecast is made. In addition, correlations depend on the fit of the estimated default probabilities to the realized default rate for given points in time.

Pages: 24 pages
Date: 2006-01-01
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Citations: View citations in EconPapers (6)

Published as: Hamerle, A., Liebig, T. and Scheule, H., 2006, "Forecasting credit event frequency - Empirical evidence for West German firms", The Journal of Risk, 9(1), 75-98

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Persistent link: https://EconPapers.repec.org/RePEc:uts:ppaper:2006-1

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