Using GEV-regression to improve accuracy of probability of default in low default portfolios
Calculating probability of default (PD) for low default portfolios in a statistically sound way can be a daunting task. For groups of coun- terparties with no or few defaults, e.g. large corporates and nancial institutions, standard approaches like logistic regression fail due to the low number of events. In this thesis, a dierent approach is used. The logit function in logistic regression is repl
