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Probability of default estimation in credit risk using mixture cure models

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

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.

Suggested Citation

  • Peláez, Rebeca & Van Keilegom, Ingrid & Cao, Ricardo & Vilar, Juan M., 2024. "Probability of default estimation in credit risk using mixture cure models," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:csdana:v:189:y:2024:i:c:s0167947323001640
    DOI: 10.1016/j.csda.2023.107853
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    References listed on IDEAS

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    5. Rebeca Peláez Suárez & Ricardo Cao Abad & Juan M. Vilar Fernández, 2021. "Correction to: Probability of default estimation in credit risk using a nonparametric approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 406-406, June.
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