Calibrating the dependence structure of the CreditRisk+ model at different time scales

The CreditRisk+ model is one of the industry standards for the valuation of credit loans portfolios or credit insurance policies. The calibration of CreditRisk+ model requires, inter alia, the specication of the parameters describing the structure of dependence of default events, loosely speaking default correlations", that { using copula functions { can be shown to correspond to a multivariate Clayton copula. This work addresses the calibration of the structure of dependence. In particular, we study the dependence of the calibration procedure on the tenor of the time series, that might have a dierent frequency with respect to the time horizon onto which the model is used for forecasting, as it is often the case in real life applications. The role of the statistical error as a function of the time series tenor is also discussed.