Volterra mortality model: Actuarial valuation and risk management with long-range dependence

Ling WANG, Mei Choi CHIU, Hoi Ying WONG

Research output: Contribution to journalArticlespeer-review

Abstract

While abundant empirical studies support the long-range dependence (LRD) of mortality rates, the corresponding impact on mortality securities is largely unknown due to the lack of appropriate tractable models for valuation and risk management purposes. We propose a novel class of Volterra mortality models that incorporate LRD into the actuarial valuation, retain tractability, and are consistent with the existing continuous-time affine mortality models. We derive the survival probability in closed-form solution by taking into account of the historical health records. The flexibility and tractability of the models make them useful in valuing mortality-related products such as death benefits, annuities, longevity bonds, and many others, as well as offering optimal mean–variance mortality hedging rules. Numerical studies are conducted to examine the effect of incorporating LRD into mortality rates on various insurance products and hedging efficiency. Copyright © 2020 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)1-14
JournalInsurance: Mathematics and Economics
Volume96
Early online date20 Oct 2020
DOIs
Publication statusE-pub ahead of print - 20 Oct 2020

Citation

Wang, L., Chiu, M. C., & Wong, H. Y. (2021). Volterra mortality model: Actuarial valuation and risk management with long-range dependence. Insurance: Mathematics and Economics, 96, 1-14. doi: 10.1016/j.insmatheco.2020.10.002

Keywords

  • Stochastic mortality
  • Long-range dependence
  • Affine Volterra processes
  • Valuation
  • Mean–variance hedging

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