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Stochastic Mortality: The Impact on Target Capital

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  • Olivieri, Annamaria
  • Pitacco, Ermanno

Abstract

In this paper, we take the point of view of an insurer dealing with life annuities, which aims at building up a (partial) internal model in order to quantify the impact of mortality risks, namely process and longevity risk, in view of taking appropriate risk management actions. We assume that a life table, providing a best-estimate assessment of annuitants' future mortality is available to the insurer; conversely, the insurer has no access to data sets and the methodology underlying the construction of the life table. Nonetheless, the insurer is aware that, in the presence of mortality risks, a stochastic approach is required. The (projected) life table, which provides a deterministic description of future mortality, should then be used as the basic input of a stochastic model. The model we propose focuses on the annual number of deaths in a given cohort, which we represent allowing for a random mortality rate. To this purpose, we adopt the widely used Poisson model, first assuming a Gamma-distributed random parameter, and second introducing time-dependence in the parameter itself. Further, we define a Bayesian-inferential procedure for updating the parameters to experience in some situations. The setting we define does not demand advanced analytical tools, while allowing for process and longevity risk in a rigorous way. The model is then implemented for capital allocation purposes. We investigate the amount of the required capital for a given life annuity portfolio, based on solvency targets which could be adopted within internal models. The outcomes of such an investigation are compared with the capital required according to some standard rules, in particular those proposed within the Solvency 2 project.

Suggested Citation

  • Olivieri, Annamaria & Pitacco, Ermanno, 2009. "Stochastic Mortality: The Impact on Target Capital," ASTIN Bulletin, Cambridge University Press, vol. 39(2), pages 541-563, November.
  • Handle: RePEc:cup:astinb:v:39:y:2009:i:02:p:541-563_00
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    Citations

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    Cited by:

    1. Liu, Yanxin & Li, Johnny Siu-Hang, 2016. "It’s all in the hidden states: A longevity hedging strategy with an explicit measure of population basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 301-319.
    2. An Chen & Montserrat Guillen & Elena Vigna, 2017. "Solvency requirement in a unisex mortality model," Carlo Alberto Notebooks 504, Collegio Carlo Alberto.
    3. Rokas Gylys & Jonas Šiaulys, 2019. "Revisiting Calibration of the Solvency II Standard Formula for Mortality Risk: Does the Standard Stress Scenario Provide an Adequate Approximation of Value-at-Risk?," Risks, MDPI, vol. 7(2), pages 1-24, May.
    4. Ronkainen, Vesa, 2012. "Stochastic modeling of financing longevity risk in pension insurance," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2012_044.
    5. Hato Schmeiser & Caroline Siegel & Joël Wagner, 2012. "The risk of model misspecification and its impact on solvency measurement in the insurance sector," Journal of Risk Finance, Emerald Group Publishing, vol. 13(4), pages 285-308, August.
    6. Raimond Maurer & Olivia S. Mitchell & Ralph Rogalla & Vasily Kartashov, 2013. "Lifecycle Portfolio Choice With Systematic Longevity Risk and Variable Investment—Linked Deferred Annuities," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(3), pages 649-676, September.
    7. Annamaria Olivieri & Ermanno Pitacco, 2012. "Life tables in actuarial models: from the deterministic setting to a Bayesian approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(2), pages 127-153, June.
    8. Lin, Tzuling & Wang, Chou-Wen & Tsai, Cary Chi-Liang, 2015. "Age-specific copula-AR-GARCH mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 110-124.
    9. Levantesi, Susanna & Menzietti, Massimiliano, 2012. "Managing longevity and disability risks in life annuities with long term care," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 391-401.
    10. Cairns, Andrew J.G., 2011. "Modelling and management of longevity risk: Approximations to survivor functions and dynamic hedging," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 438-453.
    11. Andrew J.G. Cairns & Kevin Dowd & David Blake & Guy D. Coughlan, 2014. "Longevity hedge effectiveness: a decomposition," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 217-235, February.
    12. Ronkainen, Vesa, 2012. "Stochastic modeling of financing longevity risk in pension insurance," Scientific Monographs, Bank of Finland, number 2012_044.
    13. repec:zbw:bofism:2012_044 is not listed on IDEAS
    14. D. Tabakova & E. Pitacco, 2021. "Heterogeneity and uncertainty in a multistate framework," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 117-139, June.
    15. Delong, Łukasz & Chen, An, 2016. "Asset allocation, sustainable withdrawal, longevity risk and non-exponential discounting," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 342-352.
    16. Andrew J. G. Cairns, 2013. "Robust Hedging of Longevity Risk," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(3), pages 621-648, September.

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