Worst case risk measurement: Back to the future?

M.J. Goovaerts, R. Kaas, R.J.A. Laeven

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper studies the problem of finding best-possible upper bounds on a rich class of risk measures, expressible as integrals with respect to measures, under incomplete probabilistic information. Both univariate and multivariate risk measurement problems are considered. The extremal probability distributions, generating the worst case scenarios, are also identified.

The problem of worst case risk measurement has been studied extensively by Etienne De Vijlder and his co-authors, within the framework of finite-dimensional convex analysis. This paper revisits and extends some of their results.
Original languageEnglish
Pages (from-to)380-392
JournalInsurance: Mathematics & Economics
Volume49
Issue number3
DOIs
Publication statusPublished - 2011

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Convex Analysis
Risk Measures
Dimensional Analysis
Univariate
Probability Distribution
Upper bound
Scenarios
Risk measurement
Measure of risk
Integral
Multivariate risk
Probability distribution
Convex analysis
Framework
Class

Cite this

Goovaerts, M.J. ; Kaas, R. ; Laeven, R.J.A. / Worst case risk measurement : Back to the future?. In: Insurance: Mathematics & Economics. 2011 ; Vol. 49, No. 3. pp. 380-392.
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Worst case risk measurement : Back to the future? / Goovaerts, M.J.; Kaas, R.; Laeven, R.J.A.

In: Insurance: Mathematics & Economics, Vol. 49, No. 3, 2011, p. 380-392.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Kaas, R.

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