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

doi:10.1007/s11425-016-9321-x

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 应用数学研究所

	Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models
	Liu, Xiaoqian 2; Song, Xinyuan 3; Zhou, Yong 1,4,5
刊名	SCIENCE CHINA-MATHEMATICS
	2019-12-01
卷号	62 期号:12 页码:2571-2590
关键词	DTARCH model quantile weighted composite quantile regression modified likelihood ratio test restricted WCQR estimators unrestricted WCQR estimators
ISSN号	1674-7283
DOI	10.1007/s11425-016-9321-x
英文摘要	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.
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
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000509102200010
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/50554]
专题	应用数学研究所
通讯作者	Liu, Xiaoqian
作者单位	1.East China Normal Univ, Fac Econ & Management, Acad Stat & Interdisciplinary Sci, Shanghai 200062, Peoples R China 2.Shanghai Int Studies Univ, Sch Econ & Finance, Shanghai 200083, Peoples R China 3.Chinese Univ Hong Kong, Dept Stat, Hong Kong, 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.