2023•African Journal of Applied StatisticsOpen access

Gumbel copula mortality dependence modeling

Walter Omonywa Onchere, Calvin B. Maina, Fred Nyamitago Monari

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Abstract

Using joint-life last-survivor annuities data, we conduct an analysis of the joint lifetime dependence. In the current paper, we apply the Gumbel copula and compare it to the Clayton copula approaches to address dependence effects. The method of moments procedure is used to calibrate the copula dependence parameter and maximum likelihood estimation for the marginal specifications. Subsequently, the performance of the marginals is compared following the criteria values. The findings show that the Gumbel copula with logistic marginals appropriately accounts for the dependence effects. These research findings have significant implications for the valuation of joint-life policies to avoid pricing error

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Using joint-life last-survivor annuities data, we conduct an analysis of the joint lifetime dependence. In the current paper, we apply the Gumbel copula and compare it to the Clayton copula approaches to address dependence effects. The method of moments procedure is used to calibrate the copula dependence parameter and maximum likelihood estimation for the marginal specifications. Subsequently, the performance of the marginals is compared following the criteria values. The findings show that the Gumbel copula with logistic marginals appropriately accounts for the dependence effects. These research findings have significant implications for the valuation of joint-life policies to avoid pricing error

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Available abstract

Using joint-life last-survivor annuities data, we conduct an analysis of the joint lifetime dependence. In the current paper, we apply the Gumbel copula and compare it to the Clayton copula approaches to address dependence effects. The method of moments procedure is used to calibrate the copula dependence parameter and maximum likelihood estimation for the marginal specifications. Subsequently, the performance of the marginals is compared following the criteria values. The findings show that the Gumbel copula with logistic marginals appropriately accounts for the dependence effects. These research findings have significant implications for the valuation of joint-life policies to avoid pricing error

Key concepts: Copula (linguistics), Gumbel distribution, Econometrics, Valuation (finance), Marginal distribution, Logistic regression, Joint probability distribution, Maximum likelihood

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