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Lifetime Dependence Modelling using a Truncated Multivariate Gamma Distribution

Alai, Daniel H., Landsman, Zinoviy, Sherris, Michael (2013) Lifetime Dependence Modelling using a Truncated Multivariate Gamma Distribution. Insurance: Mathematics and Economics, 52 (3). pp. 542-549. ISSN 0167-6687. (doi:10.1016/j.insmatheco.2013.03.011) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:38167)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
http://dx.doi.org/10.1016/j.insmatheco.2013.03.011

Abstract

Systematic improvements in mortality increases dependence in the survival distributions of insured lives, which is not accounted for in standard life tables and actuarial models used for annuity pricing and reserving. Systematic longevity risk also undermines the law of large numbers, a law that is relied on in the risk management of life insurance and annuity portfolios. This paper applies a multivariate gamma distribution to incorporate dependence. Lifetimes are modelled using a truncated multivariate gamma distribution that induces dependence through a shared gamma distributed component. Model parameter estimation is developed based on the method of moments and generalized to allow for truncated observations. The impact of dependence within a portfolio, or cohort, of lives with similar risk characteristics is demonstrated by applying the model to annuity valuation. Dependence is shown to have a significant impact on the risk of the annuity portfolio as compared with traditional actuarial methods that implicitly assume independent lifetimes.

Item Type: Article
DOI/Identification number: 10.1016/j.insmatheco.2013.03.011
Uncontrolled keywords: Systematic Longevity Risk; Dependence; Multivariate Gamma; Lifetime Distribution; Annuity Valuation
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Daniel Alai
Date Deposited: 05 Feb 2014 14:34 UTC
Last Modified: 16 Feb 2021 12:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/38167 (The current URI for this page, for reference purposes)

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