Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

doi:10.1016/j.envres.2016.07.015

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	Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets
	Lu, Fengbin1 ; Qiao, Han 2; Wang, Shouyang2 ; Lai, Kin Keung 3; Li, Yuze 4
	2017
发表期刊	ENVIRONMENTAL RESEARCH
ISSN	0013-9351
卷号	152 页码:351-359
摘要	This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. (C) 2016 Elsevier Ltd. All rights reserved.
关键词	Time-varying coefficient VAR Dynamic lagged correlation Granger causality Crude oil Stock market
DOI	10.1016/j.envres.2016.07.015
语种	英语
资助项目	National Natural Science Foundation of China (NSFC)[71001096] ; National Natural Science Foundation of China (NSFC)[71373262] ; National Natural Science Foundation of China (NSFC)[71390330] ; National Natural Science Foundation of China (NSFC)[71390331] ; National Natural Science Foundation of China (NSFC)[70871109] ; Center for Forecasting Science, Chinese Academy of Sciences
WOS研究方向	Environmental Sciences & Ecology ; Public, Environmental & Occupational Health
WOS类目	Environmental Sciences ; Public, Environmental & Occupational Health
WOS记录号	WOS:000389684600044
出版者	ACADEMIC PRESS INC ELSEVIER SCIENCE
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/24439
专题	系统科学研究所
通讯作者	Qiao, Han
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Econ & Management, 80 Zhongguancun East Rd, Beijing 100190, Peoples R China 3.City Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China 4.Univ Toronto, Dept Ind Engn, Toronto, ON M5S 1A1, Canada
推荐引用方式 GB/T 7714	Lu, Fengbin,Qiao, Han,Wang, Shouyang,et al. Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets[J]. ENVIRONMENTAL RESEARCH,2017,152:351-359.
APA	Lu, Fengbin,Qiao, Han,Wang, Shouyang,Lai, Kin Keung,&Li, Yuze.(2017).Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.ENVIRONMENTAL RESEARCH,152,351-359.
MLA	Lu, Fengbin,et al."Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets".ENVIRONMENTAL RESEARCH 152(2017):351-359.