Analyzing the co-movement and its spatial–temporal patterns in Chinese stock market

Hanxiao Chen, Xiaolong Zheng and Daniel Dajun Zeng

Physica A: Statistical Mechanics and its Applications, 2020, vol. 555, issue C

Abstract: The regional financial turbulence might result in the collapse of the whole financial system and could even subsequently burden the international financial markets. In this study, we mainly focus on investigating the interdependence of stocks and understanding the co-movement and its spatial–temporal patterns in Chinese stock market. Our empirical results demonstrate that the extent of co-movement between two provinces is positively influenced by their GDP on average, and negatively affected by dissimilarity of the economic structure. By constructing the Triangulated Maximally Filtered Graph and hierarchical tree, we find that western region is not as covariant as eastern region while the influence strength of a province is highly associated with its economic strength. Further, we obtain that the stock indices are stably closely connected over time, and provincial indices grow greater during the bull and bear market and move towards the direction opposite to Shanghai Stock Exchange Composite Index during the regular market oscillation period. These findings can provide for policymakers and investors significant insights into understanding the underlying interdependency of stocks and the corresponding economic factors in Chinese financial markets from the spatial–temporal perspective.

Keywords: Stock co-movement; Spatial–temporal patterns; Triangulated Maximally; Filtered Graph; Exponential weighted Pearson correlation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:555:y:2020:i:c:s0378437120303198

DOI: 10.1016/j.physa.2020.124655

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