Bootstrap tests for structural change with infinite variance observations

被引:30
作者
Jin, Hao [1 ]
Tian, Zheng [1 ,2 ]
Qin, Ruibing [1 ]
机构
[1] Northwestern Polytech Univ, Dept Appl Math, Xian 710072, Shaanxi, Peoples R China
[2] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
PARAMETER; SQUARES;
D O I
10.1016/j.spl.2009.06.008
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
070103 [概率论与数理统计]; 140311 [社会设计与社会创新];
摘要
The quest of structural change with infinite variance observations appears to be relatively common. Conventional residual CUSUM of squares test (RCUSQ) are unreliable in the presence of such behavior, having nonpivotal asymptotic null distributions. In this paper we propose a residual-based bootstrap approach to RCUSQ testing that is valid against a range of infinite variance processes. Our proposed method does not require the practitioners to specify knowledge for tailed index. Consistency and the rate of convergence for the estimated change point are also obtained. We also show via simulations that our asymptotic results provide good approximations in finite samples. In addition, we apply our results to investigate the original returns for NO.1 SDS using a historical data set that covers the period 1999-2002. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:1985 / 1995
页数:11
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