Generalized Linear Mixed Models in Portfolio Credit Risk Modelling

A crucial point in portfolio credit risk modelling is that of dependence among default events.

One way of handling this is given by Generalized Linear Mixed Models (GLMMs); a well-known concept in statistics for dealing with repeated measurements on different units. This talk gives a general introduction to GLMMs with problems relating to portfolio credit risk in mind. In this setting default probabilities or default intensities are viewed as a result of both fixed effects and random effects, where the latter are the key to dependence between counter-party defaults. By choosing the random effects suitably we obtain dependence between defaults in a given year as well as dependence between defaults in consecutive years-two kinds of dependence that have been observed in empirical default data.