Probability of default estimation in credit risk using a nonparametric approach

In this paper, four nonparametric estimators of the probability of default in credit risk are proposed and compared. They are derived from estimators of the conditional survival function for censored data. Asymptotic expressions for the bias and the variance of these probability of default estimators are derived from similar properties for the conditional survival function estimators. A simulation study shows the performance of these four estimators. Finally, an empirical study based on modified real data illustrates their practical behaviour.

Automated summary

This paper proposes and compares four nonparametric estimators of default probability in credit risk, derived from estimators of the conditional survival function for censored data. The performance of these estimators is demonstrated through simulation and empirical studies.