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Bringing parametric mortality indexes to practice: a generalized CBD model with stochastic socioeconomic differentials in mortality improvements

Author

Listed:
  • Kenneth Q. Zhou

    (Arizona State University)

  • Johnny S.-H. Li

    (The Chinese University of Hong Kong)

  • Pintao Lyu

    (Tilburg University)

Abstract

The concept of CBD mortality indexes was proposed in 2014. While it has been shown that the use of CBD mortality indexes can effectively reduce longevity risk exposures in idealized settings, the risk mitigation potential of such indexes in a more realistic environment, whereby, for example, population basis risk exists, is yet to be investigated. This research gap is addressed in this paper through the development of a generalized CBD model with stochastic socioeconomic differentials in mortality improvements. The proposed model incorporates possible co-integration effects between mortality dynamics of socioeconomic subgroups and the general population, and features a form of coherence that is less restrictive than the typically assumed full coherence. This paper is concluded with various numerical experiments that are conducted to demonstrate the possible bias in hedge effectiveness that may be resulted if the key features of the proposed model are altered.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:gpprii:v:49:y:2024:i:2:d:10.1057_s41288-024-00318-z
    DOI: 10.1057/s41288-024-00318-z
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    References listed on IDEAS

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    1. Hao, Xuemiao & Liang, Chunli & Wei, Linghua, 2017. "Evaluation of credit value adjustment in K-forward," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 95-103.
    2. Jie Wen & Torsten Kleinow & Andrew J. G. Cairns, 2020. "Trends in Canadian Mortality by Pension Level: Evidence from the CPP and QPP," North American Actuarial Journal, Taylor & Francis Journals, vol. 24(4), pages 533-561, October.
    3. Andrew J.G. Cairns & Malene Kallestrup-Lamb & Carsten P.T. Rosenskjold & David Blake & Kevin Dowd, 2016. "Modelling Socio-Economic Differences in the Mortality of Danish Males Using a New Affluence Index," CREATES Research Papers 2016-14, Department of Economics and Business Economics, Aarhus University.
    4. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    5. Li, Jackie & Li, Johnny Siu-Hang & Tan, Chong It & Tickle, Leonie, 2019. "Assessing basis risk in index-based longevity swap transactions," Annals of Actuarial Science, Cambridge University Press, vol. 13(1), pages 166-197, March.
    6. Kenneth Q. Zhou & Johnny Siu-Hang Li, 2021. "Longevity Greeks: What Do Insurers and Capital Market Investors Need to Know?," North American Actuarial Journal, Taylor & Francis Journals, vol. 25(S1), pages 66-96, February.
    7. Johnny Li & Mary Hardy, 2011. "Measuring Basis Risk in Longevity Hedges," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(2), pages 177-200.
    8. Wai-Sum Chan & Johnny Li & Jackie Li, 2014. "The CBD Mortality Indexes: Modeling and Applications," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 38-58.
    9. 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.
    10. Wen, Jie & Cairns, Andrew J.G. & Kleinow, Torsten, 2021. "Fitting multi-population mortality models to socio-economic groups," Annals of Actuarial Science, Cambridge University Press, vol. 15(1), pages 144-172, March.
    11. Tan, Chong It & Li, Jackie & Li, Johnny Siu-Hang & Balasooriya, Uditha, 2014. "Parametric mortality indexes: From index construction to hedging strategies," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 285-299.
    12. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718, December.
    13. Andrés Villegas & Steven Haberman, 2014. "On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 168-193.
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