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...
| Autores: | , , |
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| 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 |
| 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. |
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