Stationary bootstrapping realized volatility under market microstructure noise

被引：7
|
作者：
Hwang, Eunju [1 ]
Shin, Dong Wan
机构：
[1] Ewha Womans Univ, Inst Math Sci, Seoul, South Korea
来源：
ELECTRONIC JOURNAL OF STATISTICS | 2013年 / 7卷
基金：
新加坡国家研究基金会;
关键词：
Confidence interval; market microstructure noise; stationary bootstrap; HIGH-FREQUENCY DATA; WEAK DEPENDENCE; VARIANCE; CONSISTENCY;
D O I：
10.1214/13-EJS834
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：
Large-sample validity is proved for stationary bootstrapping of a bias-corrected realized volatility under market microstructure noise, which enables us to construct a bootstrap confidence interval of integrated volatility. A finite-sample simulation shows that the stationary bootstrapping confidence interval outperforms existing ones which are constructed ignoring market microstructure noise or using asymptotic normality for the bias-corrected realized volatility.
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页码：2032 / 2053
页数：22
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