Price discovery and volatility spillover with price limits in Chinese A-shares market: A truncated GARCH approach
C. J. Adcock,
C. Ye,
S. Yin and
D. Zhang
Journal of the Operational Research Society, 2019, vol. 70, issue 10, 1709-1719
Abstract:
The use of price limits by a stock exchange means that the distribution of returns is truncated. By considering a GARCH model in conjunction with a truncated distribution for the residuals, this study investigates whether price limits have an effect on price behaviour and volatility of Chinese A-shares. The analysis has been applied to A-shares traded on the Shanghai Stock Exchange (SSE) and the Shenzhen Stock Exchange (SZSE) during the period from 2004 to 2018. The results suggest the Truncated-GARCH model outperforms a conventional model and offers substantially different insights into the effect of price limits. The delayed price discovery hypothesis is not rejected for either exchange after upper price limit hits. Limited evidence supports the volatility spillover hypothesis, as just over 5% of A-shares experience an increase of volatility after upper price limit hits on both exchanges. No evidence of reduction of volatility after price limit hits is shown in the research.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2018.1542973 (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:taf:tjorxx:v:70:y:2019:i:10:p:1709-1719
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20
DOI: 10.1080/01605682.2018.1542973
Access Statistics for this article
Journal of the Operational Research Society is currently edited by Tom Archibald
More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().