Evolution of Complex Network Topology for Chinese Listed Companies Under the COVID-19 Pandemic

Kaihao Liang (), Shuliang Li (), Wenfeng Zhang (), Zhuokui Wu, Jiaying He, Mengmeng Li and Yuling Wang
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Kaihao Liang: Zhongkai University of Agriculture and Engineering
Shuliang Li: Zhongkai University of Agriculture and Engineering
Wenfeng Zhang: Zhongkai University of Agriculture and Engineering
Zhuokui Wu: Zhongkai University of Agriculture and Engineering
Jiaying He: Zhongkai University of Agriculture and Engineering
Mengmeng Li: Zhongkai University of Agriculture and Engineering
Yuling Wang: Zhongkai University of Agriculture and Engineering

Computational Economics, 2024, vol. 63, issue 3, No 8, 1136 pages

Abstract: Abstract The purpose of this study is to analyze the topological structure dynamics of the complex network of stocks before and after the outbreak of the COVID-19, so as to provide a basis for preventing financial risks. We calculate Pearson correlation coefficient between enterprises according to logarithmic rate of return and trading volume ratio of enterprises’ stocks, and then constructed a complex network of stock market price and volume before and after the outbreak of the COVID-19. First, through thresholding and heat map imaging of the correlation matrix, the change characteristics of the correlation between various industries in 2019 and 2020 are studied. Second, the node degree, average weighted degree, graph density, clustering coefficient, and average clustering coefficient are used to study the topological structure change of the complex network of stock correlation. Third, the principle of node betweenness centrality is used to analyze the characteristics of a complex network after removing the core nodes. The research shows that, first, under the influence of the COVID-19 pandemic, the correlation among industries has the characteristics of industrial clusters, that is, the correlation in a industry is strengthened. In addition to banking, the correlation between industries has weakened, and the correlation between the banking industry and other industries has strengthened. Second, the node difference in betweenness centrality of core nodes in 2020 is higher than that in 2019, indicating that the network stability in 2019 is higher than that in 2020. These two points indicate that under the influence of the COVID-19 epidemic, the complex network topology of China’s entire stock market has changed, and companies need to undertake countermeasures in the face of the crisis to effectively prevent and control systemic risks.

Keywords: Stock; Complex network; COVID-19; Network topology characteristics (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10614-023-10418-y

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