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A nonparametric conditional copula model for successive duration times, with application to insurance subscription

Abstract : We consider two dependent random times T and U, that correspond to two successive events. This setting is motivated by an application to insurance subscription, where a potential dependence exists between a time before effectiveness of the contract T, and a time U before its termination by the policyholder. The setting also extends to various types of applications involving two duration variables with some hierarchical link between the events. Indeed, since a contract can be terminated only after it becomes effective, data are subject to a particular type of censoring, where the variable U is systematically censored when the variable T is. In this framework, a nonparametric conditional copula model is considered, in the spirit of (Gijbels, Veraverbeke, & Omelka, 2011). The uniform consistency of the conditional association parameter is obtained under conditions of dependence structure and of censoring mechanism. A simulation study and a real data application show the practical behavior of the method.
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https://hal.archives-ouvertes.fr/hal-01886196
Contributor : Olivier Lopez <>
Submitted on : Tuesday, October 2, 2018 - 4:22:35 PM
Last modification on : Friday, April 10, 2020 - 5:26:47 PM
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  • HAL Id : hal-01886196, version 1

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Yohann Le Faou, Olivier Lopez. A nonparametric conditional copula model for successive duration times, with application to insurance subscription. 2018. ⟨hal-01886196⟩

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