Forecasting Credit Portfolio Risk

Arbeitspapier

The main challenge of forecasting credit default risk in loan portfolios is 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 the inclusion of variables which are correlated with the business cycle improves the forecasts of default probabilities. Asset and default correlations depend on the factors used to model default probabilities. The better the point-in-time calibration of the estimated default probabilities, the smaller the estimated correlations. Thus, correlations and default probabilities should always be estimated simultaneously.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Discussion Paper Series 2 ; No. 2004,01

Classification and Topics

• Classification: Wirtschaft ; Duration Analysis; Optimal Timing Strategies ; Banks; Depository Institutions; Micro Finance Institutions; Mortgages ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
• Subject: asset correlation ; bank regulation ; Basel II ; credit risk ; default correlation ; default probability ; logit model ; probit model ; Kreditrisiko ; Portfolio-Management ; Prognoseverfahren ; Makroökonomischer Einfluss ; Schätzung ; Deutschland

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hamerle, Alfred ; Liebig, Thilo ; Scheule, Harald
• Event: Veröffentlichung
• (who): Deutsche Bundesbank
• (where): Frankfurt a. M.
• (when): 2004

Further information

• Handle: http://hdl.handle.net/10419/19728
• Last update: 10.03.2025, 11:44 AM CET