Open Access
May 2015 Estimating failure probabilities
Holger Drees, Laurens de Haan
Bernoulli 21(2): 957-1001 (May 2015). DOI: 10.3150/13-BEJ594

Abstract

In risk management, often the probability must be estimated that a random vector falls into an extreme failure set. In the framework of bivariate extreme value theory, we construct an estimator for such failure probabilities and analyze its asymptotic properties under natural conditions. It turns out that the estimation error is mainly determined by the accuracy of the statistical analysis of the marginal distributions if the extreme value approximation to the dependence structure is at least as accurate as the generalized Pareto approximation to the marginal distributions. Moreover, we establish confidence intervals and briefly discuss generalizations to higher dimensions and issues arising in practical applications as well.

Citation

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Holger Drees. Laurens de Haan. "Estimating failure probabilities." Bernoulli 21 (2) 957 - 1001, May 2015. https://doi.org/10.3150/13-BEJ594

Information

Published: May 2015
First available in Project Euclid: 21 April 2015

zbMATH: 06445964
MathSciNet: MR3338653
Digital Object Identifier: 10.3150/13-BEJ594

Keywords: asymptotic normality , exceedance probability , failure set , homogeneity , multivariate extremes , out of sample extrapolation , peaks over threshold

Rights: Copyright © 2015 Bernoulli Society for Mathematical Statistics and Probability

Vol.21 • No. 2 • May 2015
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