Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models

doi:10.1007/s11425-016-9321-x

CSpace > 应用数学研究所

	Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models
	Liu, Xiaoqian 1; Song, Xinyuan 2; Zhou, Yong3,4,5
	2019-12-01
发表期刊	SCIENCE CHINA-MATHEMATICS
ISSN	1674-7283
卷号	62 期号:12 页码:2571-2590
摘要	The double-threshold autoregressive conditional heteroscedastic (DTARCH) model is a useful tool to measure and forecast the mean and volatility of an asset return in a financial time series. The DTARCH model can handle situations wherein the conditional mean and conditional variance specifications are piecewise linear based on previous information. In practical applications, it is important to check whether the model has a double threshold for the conditional mean and conditional heteroscedastic variance. In this study, we develop a likelihood ratio test based on the estimated residual error for the hypothesis testing of DTARCH models. We first investigate DTARCH models with restrictions on parameters and propose the unrestricted and restricted weighted composite quantile regression (WCQR) estimation for the model parameters. These estimators can be used to construct the likelihood ratio-type test statistic. We establish the asymptotic results of the WCQR estimators and asymptotic distribution of the proposed test statistics. The finite sample performance of the proposed WCQR estimation and the test statistic is shown to be acceptable and promising using simulation studies. We use two real datasets derived from the Shanghai and Shenzhen Composite Indexes to illustrate the methodology.
关键词	DTARCH model quantile weighted composite quantile regression modified likelihood ratio test restricted WCQR estimators unrestricted WCQR estimators
DOI	10.1007/s11425-016-9321-x
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[11471277] ; MOE (Ministry of Education in China) Project of Humanities and Social Sciences[15YJC910004] ; Research Grant Council of the Hong Kong Special Administration Region[GRF 14305014] ; State Key Program of National Natural Science Foundation of China[71331006] ; Major Research Plan of National Natural Science Foundation of China[91546202]
WOS研究方向	Mathematics
WOS类目	Mathematics, Applied ; Mathematics
WOS记录号	WOS:000509102200010
出版者	SCIENCE PRESS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/50555
专题	应用数学研究所
通讯作者	Liu, Xiaoqian
作者单位	1.Shanghai Int Studies Univ, Sch Econ & Finance, Shanghai 200083, Peoples R China 2.Chinese Univ Hong Kong, Dept Stat, Hong Kong, Peoples R China 3.East China Normal Univ, Fac Econ & Management, Acad Stat & Interdisciplinary Sci, Shanghai 200062, Peoples R China 4.East China Normal Univ, Fac Econ & Management, Sch Stat, Shanghai 200062, Peoples R China 5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Xiaoqian,Song, Xinyuan,Zhou, Yong. Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models[J]. SCIENCE CHINA-MATHEMATICS,2019,62(12):2571-2590.
APA	Liu, Xiaoqian,Song, Xinyuan,&Zhou, Yong.(2019).Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models.SCIENCE CHINA-MATHEMATICS,62(12),2571-2590.
MLA	Liu, Xiaoqian,et al."Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models".SCIENCE CHINA-MATHEMATICS 62.12(2019):2571-2590.