Probability of default estimation in credit risk using mixture cure models

Peláez, Rebeca; Keilegom, Ingrid Van; Cao, Ricardo; Vilar, Juan M.

Use this link to cite:

http://hdl.handle.net/2183/36259

Probability of default estimation in credit risk using mixture cure models

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Pelaez_Rebeca_2024_Probability_of_default_estimation_in_credit_risk_using_mixture_cure_models.pdf (576.69 KB)

Identifiers

URI: http://hdl.handle.net/2183/36259

DOI: 10.1016/j.csda.2023.107853

Publication date

2024-01

Authors

Peláez, Rebeca

Keilegom, Ingrid Van

Cao, Ricardo

Vilar, Juan M.

Bibliographic citation

R. Peláez, I. Van Keilegom, R. Cao, and J. M. Vilar, "Probability of default estimation in credit risk using mixture cure models", Computational Statistics and Data Analysis, Vol. 189, 107853, Jan. 2024, doi: 10.1016/j.csda.2023.107853

Abstract

[Abstract]: 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.