Mortality: a statistical approach to detect model misspecification - Archive ouverte HAL
Article Dans Une Revue Bulletin Français d'Actuariat Année : 2015

Mortality: a statistical approach to detect model misspecification

Résumé

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.
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Dates et versions

hal-01149396 , version 1 (07-05-2015)

Identifiants

  • HAL Id : hal-01149396 , version 1

Citer

Jean-Charles Croix, Frédéric Planchet, Pierre-Emmanuel Thérond. Mortality: a statistical approach to detect model misspecification. Bulletin Français d'Actuariat, 2015, 15 (29), pp.13. ⟨hal-01149396⟩

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