Probability of default estimation in credit risk using a nonparametric approach

Abstract

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.

Publication
TEST
Rebeca Peláez
Rebeca Peláez
Assistant Professor