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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, Han2; Wang, Shouyang2; Lai, Kin Keung3; Li, Yuze4
2017
Source PublicationENVIRONMENTAL RESEARCH
ISSN0013-9351
Volume152Pages:351-359
AbstractThis 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.
KeywordTime-varying coefficient VAR Dynamic lagged correlation Granger causality Crude oil Stock market
DOI10.1016/j.envres.2016.07.015
Language英语
Funding ProjectNational 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 Research AreaEnvironmental Sciences & Ecology ; Public, Environmental & Occupational Health
WOS SubjectEnvironmental Sciences ; Public, Environmental & Occupational Health
WOS IDWOS:000389684600044
PublisherACADEMIC PRESS INC ELSEVIER SCIENCE
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/24439
Collection系统科学研究所
Affiliation1.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
Recommended Citation
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.
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