Nonparametric estimation of the probability of default with double smoothing

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...

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Detalles Bibliográficos
Autores: Peláez, Rebeca, Cao, Ricardo, Vilar, Juan M.
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/397819
Acceso en línea:https://hdl.handle.net/2117/397819
https://dx.doi.org/10.2436/20.8080.02.111
Access Level:acceso abierto
Palabra clave:Mathematical statistics
Survival analysis (Biometry)
censored data
kernel method
probability of default
risk analysis
survival analysis
Estadística matemàtica--Aplicacions
Anàlisi de supervivència (Biometria)
Estadística matemàtica
62G Nonparametric inference
62N Survival analysis and censored data
62P Applications
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
Descripción
Sumario: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.