Mortality : a statistical approach to detect model misspecification - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

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, we'll introduce a specification risk supposing the mortality law true in average but subject to random variations. Finally, the suitability of our method will be assessed within this framework.
Fichier principal
Vignette du fichier
LIFE_Croix_Planchet_Therond.pdf (470.81 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00839339 , version 1 (27-06-2013)

Identifiants

  • HAL Id : hal-00839339 , version 1

Citer

Jean-Charles Croix, Frédéric Planchet, Pierre-Emmanuel Thérond. Mortality : a statistical approach to detect model misspecification. AFIR Colloquium, Jun 2013, Lyon, France. ⟨hal-00839339⟩
175 Consultations
197 Téléchargements

Partager

Gmail Facebook X LinkedIn More