The tail empirical process for long memory stochastic volatility sequences

被引:20
|
作者
Kulik, Rafal [1 ]
Soulier, Philippe [2 ]
机构
[1] Univ Ottawa, Dept Math & Stat, Ottawa, ON K1N 6N5, Canada
[2] Univ Paris 10, Dept Math, F-92000 Nanterre, France
基金
加拿大自然科学与工程研究理事会;
关键词
Long memory; Tail empirical process; Hill estimator; Tail empirical distribution function; Stochastic volatility; RANGE DEPENDENT SEQUENCES; CONVERGENCE;
D O I
10.1016/j.spa.2010.09.001
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper describes the limiting behaviour of tail empirical processes associated with long memory stochastic volatility models We show that such a process has dichotomous behaviour, according to an interplay between the Hurst parameter and the tail index On the other hand the tail empirical process with random levels never suffers from long memory This is very desirable from a practical point of view since such a process may be, used to construct the Hill estimator of the tall index To prove our results we need to establish new results for regularly varying distributions which may be of Independent interest (c) 2010 Elsevier B V All rights reserved
引用
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页码:109 / 134
页数:26
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