EVT-Based Estimation of Risk Capital and Convergence of High Quantiles
We discuss some issues regarding the accuracy of a quantile-based estimation of risk capital. In this context, extreme value theory (EVT) emerges naturally. The paper sheds some further light on the ongoing discussion concerning the use of a semi-parametric approach like EVT and the use of specific...
| Veröffentlicht in: | Advances in Applied Probability. - Applied Probability Trust. - 40(2008), 3, Seite 696-715 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2008
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| Zugriff auf das übergeordnete Werk: | Advances in Applied Probability |
| Schlagworte: | Extreme value theory g-and-h distribution operational risk peaks over threshold penultimate approximation second-order regular variation slow variation value at risk Mathematics Economics |
| Zusammenfassung: | We discuss some issues regarding the accuracy of a quantile-based estimation of risk capital. In this context, extreme value theory (EVT) emerges naturally. The paper sheds some further light on the ongoing discussion concerning the use of a semi-parametric approach like EVT and the use of specific parametric models such as the g-and-h. In particular, we discusses problems and pitfalls evolving from such parametric models when using EVT and highlight the importance of the underlying second-order tail behavior. |
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| ISSN: | 00018678 |