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| Titel |
Modelling clustering of natural hazard phenomena and the effect on re/insurance loss perspectives |
| VerfasserIn |
S. Khare, A. Bonazzi, C. Mitas, S. Jewson |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 15, no. 6 ; Nr. 15, no. 6 (2015-06-26), S.1357-1370 |
| Datensatznummer |
250119542
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| Publikation (Nr.) |
 copernicus.org/nhess-15-1357-2015.pdf |
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| Zusammenfassung |
| In this paper, we present a conceptual framework for modelling clustered natural hazards that makes
use of historical event data as a starting point. We review a methodology for modelling clustered
natural hazard processes called Poisson mixtures. This methodology is suited to the application
we have in mind as it naturally models processes that yield cross-event correlation (unlike homogeneous
Poisson models), has a high degree of tunability to the problem at hand and is analytically tractable.
Using European windstorm data as an example, we provide evidence that the
historical data show strong evidence of clustering. We then develop Poisson and Clustered
simulation models for the data, demonstrating clearly the superiority of the Clustered model which
we have implemented using the Poisson mixture approach. We then discuss the implications
of including clustering in models of prices of catXL contracts, one of the most commonly used
mechanisms for transferring risk between primary insurers and reinsurers. This paper provides
a number of unique insights into the impact clustering has on modelled catXL contract prices.
The simple modelling example in this paper provides a clear and insightful starting
point for practitioners tackling more complex natural hazard risk problems. |
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