Nonparametric estimation of the probability of default with double smoothing
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Nonparametric estimation of the probability of default with double smoothingDate
2021Citation
Peláez, Rebeca; Cao, Ricardo; Vilar, Juan M. “Nonparametric estimation of the probability of default with double smoothing”. SORT-Statistics and Operations Research Transactions, 2021, Vol. 45, Num. 2, pp. 93-120, https://doi.org/10.2436/20.8080.02.111.
Abstract
[Abstract]: 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.
Keywords
censored data
kernel method
probability of default
risk analysis
urvival analysis
kernel method
probability of default
risk analysis
urvival analysis
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From February 2013 articles are under a Creative Commons license: CC BY-NC-ND
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Atribución-NoComercial-SinDerivadas 3.0 España