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Composite quantile regression estimation for P-GARCH processes

文献类型：期刊论文

作者Zhao Biao1; Chen Zhao2; Tao GuiPing3; Chen Min4
刊名SCIENCE CHINA-MATHEMATICS
出版日期2016-05-01
卷号59期号:5页码:977-998
关键词composite quantile regression periodic GARCH process strictly periodic stationarity strong consistency asymptotic normality
ISSN号1674-7283
DOI10.1007/s11425-015-5115-0
英文摘要We consider the periodic generalized autoregressive conditional heteroskedasticity (P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator. The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions. The proposed methodology is also illustrated by VaR on stock price data.
资助项目National Natural Science Foundation of China[11371354] ; Key Laboratory of Random Complex Structures and Data Science, Chinese Academy of Sciences[2008DP173182] ; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000374329000012
出版者SCIENCE PRESS
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/22528]  
专题应用数学研究所
通讯作者Chen Zhao
作者单位1.Univ Sci & Technol China, Dept Stat & Finance, Hefei 230026, Peoples R China
2.Penn State Univ, Dept Stat, University Pk, PA 16802 USA
3.Capital Univ Econ & Business, Sch Stat, Beijing 100070, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhao Biao,Chen Zhao,Tao GuiPing,et al. Composite quantile regression estimation for P-GARCH processes[J]. SCIENCE CHINA-MATHEMATICS,2016,59(5):977-998.
APA Zhao Biao,Chen Zhao,Tao GuiPing,&Chen Min.(2016).Composite quantile regression estimation for P-GARCH processes.SCIENCE CHINA-MATHEMATICS,59(5),977-998.
MLA Zhao Biao,et al."Composite quantile regression estimation for P-GARCH processes".SCIENCE CHINA-MATHEMATICS 59.5(2016):977-998.

入库方式： OAI收割

来源：数学与系统科学研究院

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