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Asymmetry in mortality volatility and its implications on index-based longevity hedging

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  • Zhou, Kenneth Q.
  • Li, Johnny Siu-Hang

Abstract

Mortality volatility is crucially important to many aspects of index-based longevity hedging, including instrument pricing, hedge calibration and hedge performance evaluation. This paper sets out to develop a deeper understanding of mortality volatility and its implications on index-based longevity hedging. First, we study the potential asymmetry in mortality volatility by considering a wide range of generalised autoregressive conditional heteroskedasticity (GARCH)-type models that permit the volatility of mortality improvement to respond differently to positive and negative mortality shocks. We then investigate how the asymmetry of mortality volatility may impact index-based longevity hedging solutions by developing an extended longevity Greeks framework, which encompasses longevity Greeks for a wider range of GARCH-type models, an improved version of longevity vega, and a new longevity Greek known as “dynamic Delta”. Our theoretical work is complemented by two real-data illustrations, the results of which suggest that the effectiveness of an index-based longevity hedge could be significantly impaired if the asymmetry in mortality volatility is not taken into account when the hedge is calibrated.

Suggested Citation

  • Zhou, Kenneth Q. & Li, Johnny Siu-Hang, 2020. "Asymmetry in mortality volatility and its implications on index-based longevity hedging," Annals of Actuarial Science, Cambridge University Press, vol. 14(2), pages 278-301, September.
    • Handle: RePEc:cup:anacsi:v:14:y:2020:i:2:p:278-301_3
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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. Samuel Asante Gyamerah & Janet Arthur & Saviour Worlanyo Akuamoah & Yethu Sithole, 2023. "Measurement and Impact of Longevity Risk in Portfolios of Pension Annuity: The Case in Sub Saharan Africa," FinTech, MDPI, vol. 2(1), pages 1-20, January.
    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.

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