Electronic International Standard Serial Number (EISSN)
2013-8830
abstract
In this paper, a general nonparametric estimator of the probability of default is proposed and studied. It is derived from an estimator of the conditional survival function for censored data obtained with a double smoothing, on the covariate and on the variable of interest. An empirical study, based on modified real data, illustrates its practical application and a simulation study shows the performance of the proposed estimator and compares its behaviour with smoothed estimators only in the covariate. Asymptotic expressions for the bias and the variance of the probability of default estimator are found and asymptotic normality is proved.
Classification
subjects
Mathematics
Statistics
keywords
censored data; kernel method; probability of default; risk analysis; survival analysis