Iterative Adjustment of Survival Functions by Composed Probability Distortions

Alexis Bienvenüe () and Didier Rulliere ()
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Alexis Bienvenüe: LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon

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Abstract: We introduce a parametric class of composite probability distortions that can be combined to converge to a target survival function. These distortions respect analytic invertibility and stability, which are shown to be relevant in many actuarial fields. We study the asymptotic impact of such distortions on hazard rates. The paper provides an estimation methodology, including hints for initialisation. Some applications to survival data bring results for catastrophic event impact modelling. We also obtain accurate parametric representations of the mortality trend over years. Finally, we suggest a prospective mortality simulation model that comes naturally from the above analysis.

Keywords: probability distortions; mortality; iterated compositions; hyperbolic transform; risk measure; survival function transformation (search for similar items in EconPapers)
Date: 2012
Note: View the original document on HAL open archive server: https://hal.science/hal-00665890v1
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Published in The Geneva Risk and Insurance Review, 2012, 37 (2), pp.156-179. ⟨10.1057/grir.2011.7⟩

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Journal Article: Iterative Adjustment of Survival Functions by Composed Probability Distortions (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00665890

DOI: 10.1057/grir.2011.7

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