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| Titel |
Rapidly assessing the probability of exceptionally high natural hazard losses |
| VerfasserIn |
Isabella Gollini, Jonathan Rougier |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250089882
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| Publikation (Nr.) |
 EGU/EGU2014-4095.pdf |
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| Zusammenfassung |
| One of the objectives in catastrophe modeling is to assess the probability distribution of
losses for a specified period, such as a year. From the point of view of an insurance company,
the whole of the loss distribution is interesting, and valuable in determining insurance
premiums. But the shape of the righthand tail is critical, because it impinges on the
solvency of the company. A simple measure of the risk of insolvency is the probability
that the annual loss will exceed the company’s current operating capital. Imposing
an upper limit on this probability is one of the objectives of the EU SolvencyII
directive.
If a probabilistic model is supplied for the loss process, then this tail probability can be
computed, either directly, or by simulation. This can be a lengthy calculation for complex
losses. Given the inevitably subjective nature of quantifying loss distributions, computational
resources might be better used in a sensitivity analysis. This requires either a quick
approximation to the tail probability or an upper bound on the probability, ideally a tight one.
We present several different bounds, all of which can be computed nearly instantly from a
very general event loss table. We provide a numerical illustration, and discuss the conditions
under which the bound is tight. Although we consider the perspective of insurance and
reinsurance companies, exactly the same issues concern the risk manager, who is typically
very sensitive to large losses. |
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