Network analysis of the Chinese stock market during the turbulence of 2015–2016 using log-returns, volumes and mutual information

Arash Sioofy Khoojine and Dong Han

Physica A: Statistical Mechanics and its Applications, 2019, vol. 523, issue C, 1091-1109

Abstract: We use mutual information and symbolization method of time series to construct minimum spanning tree of the financial network of log-returns and trading volumes of the top 110 companies on the Chinese stock market listed on the CSI 300 index from January 2014 to December 2017 to analyze the Chinese stock market’s turbulence during 2015 to 2016. We construct three minimum spanning trees of pre-turbulence, turbulence and post-turbulence. The findings show that minimum spanning tree of turbulence has the significant differences in topological characteristics and network’s measures with pre-turbulence and post-turbulence networks. Furthermore, the pre-turbulence network is robust against nodes attack while turbulence network is fragile against it.

Keywords: Network analysis; Financial crisis; Chinese stock market; Mutual information; Symbolic time-series; Minimum spanning tree (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:523:y:2019:i:c:p:1091-1109

DOI: 10.1016/j.physa.2019.04.128

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