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Mortality: a statistical approach to detect model misspecification

Author

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  • Jean-Charles Croix

    (LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Frédéric Planchet

    (LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Pierre-Emmanuel Thérond

    (LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

Abstract

The Solvency 2 advent and the best-estimate methodology in future cash-flows valuation lead insurers to focus particularly on their assumptions. In mortality, hypothesis are critical as insurers use best-estimate laws instead of standard mortality tables. Backtesting methods, i.e. ex-post modelling validation processes , are encouraged by regulators and rise an increasing interest among practitioners and academics. In this paper, we propose a statistical approach (both parametric and non-parametric models compliant) for mortality laws backtesting under model risk. Afterwards, a specification risk is introduced assuming that the mortality law is subject to random variations. Finally, the suitability of the proposed method will be assessed within this framework.

Suggested Citation

  • Jean-Charles Croix & Frédéric Planchet & Pierre-Emmanuel Thérond, 2015. "Mortality: a statistical approach to detect model misspecification," Post-Print hal-01149396, HAL.
    • Handle: RePEc:hal:journl:hal-01149396
    Note: View the original document on HAL open archive server: https://hal.science/hal-01149396v1
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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.

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