Oil Prices and Chinese Stock Market: Nonlinear Causality and Volatility Persistence

Fenghua Wen, Jihong Xiao, Xiao-Hua Xia, Bin Chen, Zhengyan Xiao and Jinyi Li

Emerging Markets Finance and Trade, 2019, vol. 55, issue 6, 1247-1263

Abstract: This article mainly focuses on investigating the nonlinear co-integration and nonlinear causality relationships between oil prices and Chinese stock market at the overall and sectoral levels by using nonlinear autoregressive distributed lags (NARDL) model and Diks and Panchenko (DP) test. The empirical results show that there are not significantly asymmetric co-integration effects between oil prices and Chinese stock market for the overall and sectoral levels. However, the significantly nonlinear causality between oil prices and Chinese stock market can be found. Specifically, oil prices can widely affect Chinese stock indices through nonlinear channel. The cases in the reverse also work for overall indices and Mining, Utilities, Financial and Real Estate sectors. Furthermore, the potential sources of these nonlinear causality linkages are examined. The results suggest that volatility persistence rather than asymmetrical co-integration is the major factor that accounts for the nonlinear causality between oil prices and Chinese stock market.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (49)

Downloads: (external link)
http://hdl.handle.net/10.1080/1540496X.2018.1496078 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mes:emfitr:v:55:y:2019:i:6:p:1247-1263

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/MREE20

DOI: 10.1080/1540496X.2018.1496078

Access Statistics for this article

More articles in Emerging Markets Finance and Trade from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().