Open Access
August 2006 Confidence regions for high quantiles of a heavy tailed distribution
Liang Peng, Yongcheng Qi
Ann. Statist. 34(4): 1964-1986 (August 2006). DOI: 10.1214/009053606000000416


Estimating high quantiles plays an important role in the context of risk management. This involves extrapolation of an unknown distribution function. In this paper we propose three methods, namely, the normal approximation method, the likelihood ratio method and the data tilting method, to construct confidence regions for high quantiles of a heavy tailed distribution. A simulation study prefers the data tilting method.


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Liang Peng. Yongcheng Qi. "Confidence regions for high quantiles of a heavy tailed distribution." Ann. Statist. 34 (4) 1964 - 1986, August 2006.


Published: August 2006
First available in Project Euclid: 3 November 2006

zbMATH: 1246.62125
MathSciNet: MR2283723
Digital Object Identifier: 10.1214/009053606000000416

Primary: 62G32
Secondary: 62G02

Keywords: confidence region , data tilting , Empirical likelihood method , heavy tail , high quantile

Rights: Copyright © 2006 Institute of Mathematical Statistics

Vol.34 • No. 4 • August 2006
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