Probability of default estimation in credit risk using mixture cure models

被引：1

作者：

Pelaez, Rebeca ^{[1
]}

Van Keilegom, Ingrid ^{[2
]}

Cao, Ricardo ^{[3
]}

Vilar, Juan M. ^{[3
]}

机构：

[1] Univ Carlos III Madrid, Dept Stat, Madrid, Spain

[2] Katholieke Univ Leuven, Res Ctr Operat Res & Stat ORSTAT, Leuven, Belgium

[3] Univ A Coruna, Dept Math, Res Grp MODES, CITIC, La Coruna, Spain

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2024年 / 189卷

基金：

欧洲研究理事会;

关键词：

Censored data; Survival analysis; Nonparametric estimation; Kernel method; BOOTSTRAP BANDWIDTH SELECTION; SURVIVAL ANALYSIS; NONPARAMETRIC-ESTIMATION;

D O I：

10.1016/j.csda.2023.107853

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

An estimator of the probability of default (PD) in credit risk is proposed. It is derived from a nonparametric conditional survival function estimator based on cure models. Asymptotic expressions for the bias and the variance, as well as the asymptotic normality of the proposed estimator are presented. A simulation study shows the performance of the nonparametric estimator compared with Beran's PD estimator and other semiparametric methods. Finally, an empirical study based on modified real data illustrates the practical behaviour.(c) 2023 Published by Elsevier B.V.

引用

页数：23

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