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A Cautionary Note on Natural Hedging of Longevity Risk

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  • Nan Zhu
  • Daniel Bauer

Abstract

In this article, we examine the so-called natural hedging approach for life insurers to internally manage their longevity risk exposure by adjusting their insurance portfolio. In particular, unlike the existing literature, we also consider a nonparametric mortality forecasting model that avoids the assumption that all mortality rates are driven by the same factor(s).Our primary finding is that higher order variations in mortality rates may considerably affect the performance of natural hedging. More precisely, although results based on a parametric single factor model—in line with the existing literature—imply that almost all longevity risk can be hedged, results are far less encouraging for the nonparametric mortality model. Our finding is supported by robustness tests based on alternative mortality models.

Suggested Citation

  • Nan Zhu & Daniel Bauer, 2014. "A Cautionary Note on Natural Hedging of Longevity Risk," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 104-115.
  • Handle: RePEc:taf:uaajxx:v:18:y:2014:i:1:p:104-115
    DOI: 10.1080/10920277.2013.876911
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    Cited by:

    1. Debonneuil, Edouard & Loisel, Stéphane & Planchet, Frédéric, 2018. "Do actuaries believe in longevity deceleration?," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 325-338.
    2. 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.
    3. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    4. Blake, David & El Karoui, Nicole & Loisel, Stéphane & MacMinn, Richard, 2018. "Longevity risk and capital markets: The 2015–16 update," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 157-173.
    5. Zhou, Hongjuan & Zhou, Kenneth Q. & Li, Xianping, 2022. "Stochastic mortality dynamics driven by mixed fractional Brownian motion," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 218-238.
    6. Cupido, Kyran & Jevtić, Petar & Paez, Antonio, 2020. "Spatial patterns of mortality in the United States: A spatial filtering approach," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 28-38.
    7. M. Martin Boyer & Lars Stentoft, 2017. "Yes We Can (Price Derivatives on Survivor Indices)," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 20(1), pages 37-62, March.

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