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Large Quantile Estimation in a Multivariate Setting

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Author Info
Dehaan, L.
Huang, X.
Abstract

An asymptotic theory is developed for the estimation of high quantile curves, i.e., sets of points in higher dimensional space for which the exeedance probability is pn, with npn --> 0 (n --> [infinity]). Here n is the number of available observations. This is the situation of interest if one wants to protect against a calamity that has not yet occurred. Asymptotic normality of the estimated quantile curve is proved under appropriate conditions, including the domain of the attraction condition for multivariate extremes.

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Publisher Info
Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 53 (1995)
Issue (Month): 2 (May)
Pages: 247-263
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Handle: RePEc:eee:jmvana:v:53:y:1995:i:2:p:247-263

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  1. Einmahl, J.H.J. & Haan, L.F.M. de, 2009. "Estimating Extreme Bivariate Quantile Regions," Discussion Paper 2009-29, Tilburg University, Center for Economic Research. [Downloadable!]
  2. Giuseppe Arbia, 2000. "Estimation Of Market Risk In Case Of Non-Gaussian Asset'S Returns," Departmental Working Papers 133, Tor Vergata University, CEIS. [Downloadable!]
  3. Einmahl, John H.J. & Li, Jun & Liu, Regina Y., 2006. "Extreme value theory approach to simultaneous monitoring and tresholding of multiple risk indicators," Discussion Paper 104, Tilburg University, Center for Economic Research. [Downloadable!]
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This page was last updated on 2009-12-30.


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