ESTIMATING THE DEGREE OF ACTIVITY OF JUMPS IN HIGH FREQUENCY DATA

被引：181

作者：

Ait-Sahalia, Yacine ^{[1
,2
]}

Jacod, Jean ^{[3
]}

机构：

[1] Princeton Univ, Dept Econ, Princeton, NJ 08544 USA

[2] NBER, Princeton, NJ 08544 USA

[3] Univ Paris 06, CNRS, UMR 7586, Inst Math Jussieu, F-75252 Paris 05, France

来源：

ANNALS OF STATISTICS | 2009年 / 37卷 / 5A期

基金：

美国国家科学基金会;

关键词：

Jumps; index of activity; infinite activity; discrete sampling; high frequency; LEVY PROCESSES; TAIL;

D O I：

10.1214/08-AOS640

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：

We define a generalized index of jump activity, propose estimators of that index for a discretely sampled process and derive the estimators' properties. These estimators are applicable despite the presence of Brownian volatility in the process, which makes it more challenging to infer the characteristics of the small, infinite activity jumps. When the method is applied to high frequency stock returns, we find evidence of infinitely active jumps in the data and estimate their index of activity.

引用

页码：2202 / 2244

页数：43

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