Subsampling the distribution of diverging statistics with applications to finance

被引:14
作者
Bertail, P
Haefke, C
Politis, DN
White, H [1 ]
机构
[1] Univ Calif San Diego, Dept Econ, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Dept Math, La Jolla, CA 92093 USA
[3] CREST, Stat Lab, F-94205 Malakoff, France
[4] Univ Pompeu Fabra, Dept Econ & Business, Barcelona 08005, Spain
基金
美国国家科学基金会;
关键词
resampling methods; extreme value statistics; Value at Risk; portfolio selection;
D O I
10.1016/S0304-4076(03)00215-X
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known or unknown rates when the underlying time series is strictly stationary and strong mixing. Based on our results we provide a detailed discussion of how to estimate extreme order statistics with dependent data and present two applications to assessing financial market risk. Our method performs well in estimating Value at Risk and provides a superior alternative to Hill's estimator in operationalizing Safety First portfolio selection. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:295 / 326
页数:32
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