Journal of Risk

Forecasting credit event frequency – empirical evidence for West German firms

Alfred Hamerle, Thilo Liebig, Harald Scheule


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.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

If you already have an account, please sign in here.

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here