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The Risk of a Mortality Catastrophe

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  • Daniel Bauer
  • Florian Kramer

Abstract

We develop a continuous-time model for analyzing and valuing catastrophe mortality contingent claims based on stochastic modeling of the force of mortality. We derive parameter estimates from a 105-year time series of U.S. population mortality data using a simulated maximum likelihood approach based on a particle filter. Relying on the resulting parameters, we calculate loss profiles for a representative catastrophe mortality transaction and compare them to the “official” loss profiles that are provided by the issuers to investors and rating agencies. We find that although the loss profiles are subject to great uncertainties, the official figures fall significantly below the corresponding risk statistics based on our model. In particular, we find that the annualized incidence probability of a mortality catastrophe, defined as a 15% increase in aggregated mortality probabilities, is about 1.4%—compared to about 0.1% according to the official loss profiles.

Suggested Citation

  • Daniel Bauer & Florian Kramer, 2016. "The Risk of a Mortality Catastrophe," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 391-405, July.
    • Handle: RePEc:taf:jnlbes:v:34:y:2016:i:3:p:391-405
    DOI: 10.1080/07350015.2015.1040117
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    Cited by:

    1. Li, Han & Liu, Haibo & Tang, Qihe & Yuan, Zhongyi, 2023. "Pricing extreme mortality risk in the wake of the COVID-19 pandemic," Insurance: Mathematics and Economics, Elsevier, vol. 108(C), pages 84-106.
    2. Masako Ikefuji & Roger J. A. Laeven & Jan R. Magnus & Yuan Yue, 2022. "Earthquake Risk Embedded in Property Prices: Evidence From Five Japanese Cities," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(537), pages 82-93, January.

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