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Constructing Out-of-the-Money Longevity Hedges Using Parametric Mortality Indexes

Author

Listed:
  • Johnny Siu-Hang Li
  • Jackie Li
  • Uditha Balasooriya
  • Kenneth Q. Zhou

Abstract

Proposed by Chan, Li, and Li, parametric mortality indexes (i.e., indexes created using the time-varying parameters in a suitable stochastic mortality model) can be used to develop tradable mortality-linked derivatives such as K-forwards. Compared to existing indexes such as the Life and Longevity Markets Association’s LifeMetrics, parametric mortality indexes are richer in information content, allowing the market to better concentrate liquidity. In this article, we further study this concept in several aspects. First, we consider options written on parametric mortality indexes. Such options enable hedgers to create out-of-the-money longevity hedges, which, compared to at-the-money-hedges created with q-/K-forwards, may better meet hedgers’ needs for protection against downside risk. Second, using the properties of the time series processes for the parametric mortality indexes, we derive analytical risk-neutral pricing formulas for K-forwards and options. In addition to convenience, the analytical pricing formulas remove the need for computationally intensive nested simulations that are entailed in, for example, the calculation of the hedging instruments’ values when a dynamic hedge is adjusted. Finally, we construct static and dynamic Greek hedging strategies using K-forwards and options, and demonstrate empirically the conditions under which an out-of-the-money hedge is more economically justifiable than an at-the-money one.

Suggested Citation

  • Johnny Siu-Hang Li & Jackie Li & Uditha Balasooriya & Kenneth Q. Zhou, 2021. "Constructing Out-of-the-Money Longevity Hedges Using Parametric Mortality Indexes," North American Actuarial Journal, Taylor & Francis Journals, vol. 25(S1), pages 341-372, February.
  • Handle: RePEc:taf:uaajxx:v:25:y:2021:i:s1:p:s341-s372
    DOI: 10.1080/10920277.2019.1650285
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    Citations

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    Cited by:

    1. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Kenneth Q. Zhou & Johnny S.-H. Li & Pintao Lyu, 2024. "Bringing parametric mortality indexes to practice: a generalized CBD model with stochastic socioeconomic differentials in mortality improvements," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 295-319, April.
    3. Yang Qiao & Chou-Wen Wang & Wenjun Zhu, 2024. "Machine learning in long-term mortality forecasting," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 340-362, April.
    4. Feng, Ben Mingbin & Li, Johnny Siu-Hang & Zhou, Kenneth Q., 2022. "Green nested simulation via likelihood ratio: Applications to longevity risk management," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 285-301.
    5. Shuai Yang & Kenneth Q. Zhou, 2023. "On Risk Management of Mortality and Longevity Capital Requirement: A Predictive Simulation Approach," Risks, MDPI, vol. 11(12), pages 1-18, November.
    6. Xiaobai Zhu & Kenneth Q. Zhou & Zijia Wang, 2024. "A new paradigm of mortality modeling via individual vitality dynamics," Papers 2407.15388, arXiv.org, revised Oct 2024.

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