夫妻依赖死亡时间的两种混合模型:一种常见的冲击方法

IF 1.6 3区 经济学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Zied Chaieb, Domenico De Giovanni, Djibril Gueye
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Calibration is done on the data of joint life contracts from a Canadian company.Keywords: Intensity-based modelsdependence structurefatal shock eventsjoint life insurance AcknowledgmentsThis paper has benefited from the valuable comments of one anonymous reviewer, whom the authors wish to thank. The remaining errors are the authors' only responsibility.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Throughout the paper x and y denote the ages of the husband and wife, respectively.2 Here, we have considered the independent case just for simplicity, but we could also consider, in the same spirit, the dependent case for the joint survival function using a copula function.3 In our setup, we have P(τx>s|Ft)=E[e−Γsx|FtW]E[e−Ks|FtK]. Analogous calculations can be done for the marginal probability P(τy>s|Ft).4 The authors wish to thank the Society of Actuaries, through the courtesy of Edward (Jed) Frees and Emiliano A. 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引用次数: 0

摘要

摘要本文结合两个最新的信用风险模型,利用Marshall-Olkin设置来捕捉二元生存函数的依赖结构。这种方法的主要优点是在依赖结构中处理致命冲击事件,因为这两种信用风险模型允许将个体的死亡时间与灾难时间事件相匹配。我们还提供了一种将其他依赖源添加到我们的方法中的方法。在这种情况下,我们推导了一些普通人寿保险产品的无套利价格。我们通过研究Sibuya的依赖函数来证明我们的方法的性能。校准是根据加拿大一家公司的联合寿命合同数据完成的。关键词:基于强度的模型;依赖性;结构性冲击事件;共同人寿保险。剩下的错误是作者唯一的责任。披露声明作者未报告潜在的利益冲突。注1在整个论文中,x和y分别表示丈夫和妻子的年龄这里,为了简单起见,我们考虑了独立的情况,但我们也可以考虑,同样的精神,联合生存函数的相关情况,使用一个联结函数在我们的设置中,我们有P(τx>s|Ft)=E[E−Γsx|FtW]E[E−Ks|FtK]。边际概率P(τy>s |ft)也可以进行类似的计算作者希望感谢精算师协会,感谢Edward (Jed) Frees和Emiliano A. Valdez提供本文中的数据这种边际生存概率的函数形式来自于假设随机强度为dμh(u)=ahμh(u)+σhμh(h)dWh(u),其中a为σ>0。Sh(u;t)是有效生存函数的充分条件是σ2<2dc。关于该模型的更多细节可以在Luciano et al. (Citation2008), Luciano & Vigna (Citation2005)中找到Luciano et al. (Citation2008)将这种关联模型称为4.2.20 nelson copula函数。最初由Nelsen (Citation2007)提出,详细的研究可以在Spreeuw (Citation2006)中找到。选择这种特殊的关联模型是因为它对本文使用的数据产生了几个阿基米德copula的最佳拟合(Luciano等)。Citation2008)。domenico De Giovanni感谢PNRR项目“意大利老龄化,Age-It”(PE0000015 - CUP H73C22000900006)和意大利大学和研究部的资金支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two hybrid models for dependent death times of couple: a common shock approach
AbstractWe combine two recent credit risk models with the Marshall–Olkin setup to capture the dependence structure of bivariate survival functions. The main advantage of this approach is to handle fatal shock events in the dependence structure since these two credit risk models allow one to match the time of death of an individual with a catastrophe time event. We also provide a methodology for adding other sources of dependency to our approach. In such a setup, we derive the no-arbitrage prices of some common life insurance products for coupled lives. We demonstrate the performance of our method by investigating Sibuya's dependence function. Calibration is done on the data of joint life contracts from a Canadian company.Keywords: Intensity-based modelsdependence structurefatal shock eventsjoint life insurance AcknowledgmentsThis paper has benefited from the valuable comments of one anonymous reviewer, whom the authors wish to thank. The remaining errors are the authors' only responsibility.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Throughout the paper x and y denote the ages of the husband and wife, respectively.2 Here, we have considered the independent case just for simplicity, but we could also consider, in the same spirit, the dependent case for the joint survival function using a copula function.3 In our setup, we have P(τx>s|Ft)=E[e−Γsx|FtW]E[e−Ks|FtK]. Analogous calculations can be done for the marginal probability P(τy>s|Ft).4 The authors wish to thank the Society of Actuaries, through the courtesy of Edward (Jed) Frees and Emiliano A. Valdez, for making available the data in this paper.5 This functional form of the marginal survival probability comes from assuming a stochastic intensity of the form dμh(u)=ahμh(u)+σhμh(h)dWh(u), with a,σ>0. A sufficient condition for Sh(u;t) to be a valid survival function is σ2<2dc. Additional details about this model can be found in Luciano et al. (Citation2008), Luciano & Vigna (Citation2005).6 Luciano et al. (Citation2008) refers to this model of association as the 4.2.20 Nelsen copula function. Originally proposed in Nelsen (Citation2007), a detailed study can be found in Spreeuw (Citation2006). The choice of this particular model of association is because it produces the best fit in a range of several Archimedean copulas for the data used in this paper (Luciano et al. Citation2008).Additional informationFundingDomenico De Giovanni gratefully acknowledges financial support from the PNRR project ‘Italian Ageing, Age-It’ (PE0000015 - CUP H73C22000900006) and Ministry of University and Research of Italy.
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来源期刊
Scandinavian Actuarial Journal
Scandinavian Actuarial Journal MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
3.30
自引率
11.10%
发文量
38
审稿时长
>12 weeks
期刊介绍: Scandinavian Actuarial Journal is a journal for actuarial sciences that deals, in theory and application, with mathematical methods for insurance and related matters. The bounds of actuarial mathematics are determined by the area of application rather than by uniformity of methods and techniques. Therefore, a paper of interest to Scandinavian Actuarial Journal may have its theoretical basis in probability theory, statistics, operations research, numerical analysis, computer science, demography, mathematical economics, or any other area of applied mathematics; the main criterion is that the paper should be of specific relevance to actuarial applications.
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