Impact of correlation crises in risk theory

Romain Biard (), Claude Lefèvre () and Stéphane Loisel
Additional contact information
Romain Biard: LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon
Claude Lefèvre: ULB - Département de Mathématique [Bruxelles] - ULB - Faculté des Sciences [Bruxelles] - ULB - Université libre de Bruxelles

Post-Print from HAL

Abstract: In the renewal risk model, several strong hypotheses may be found too restrictive to model accurately the complex evolution of the reserves of an insurance company. In the case where claim sizes are heavy-tailed, we relax independence and stationarity assumptions and extend some asymptotic results on finite-time ruin probabilities, to take into account possible correlation crises like the one recently bred by the sub-prime crisis: claim amounts, in general assumed to be independent, may suddenly become strongly positively dependent. The impact of dependence and non-stationarity is analyzed and several concrete examples are given.

Keywords: Finite-time ruin probabilities; ruin theory; correlation crisis; Sub-prime effect; processes with dependent increments; asymptotic behavior; non-stationarity; heavy-tailed claim size distribution (search for similar items in EconPapers)
Date: 2008
Note: View the original document on HAL open archive server: https://hal.science/hal-00308782v1
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Published in Insurance: Mathematics and Economics, 2008, 43 (3), pp.412-421

Downloads: (external link)
https://hal.science/hal-00308782v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00308782

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().