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基于复杂网络的中国金融子市场间风险传染研究

Research on Risk Contagion among Financial Submarkets in China Based on Complex Networks.

作者信息

Xu Yuhua, Zhao Yue, Liu Mengna, Xie Chengrong

机构信息

School of Finance, Nanjing Audit University, Nanjing 211815, China.

School of Statistics and Mathematics, Nanjing Audit University, Nanjing 211815, China.

出版信息

Entropy (Basel). 2022 Aug 14;24(8):1120. doi: 10.3390/e24081120.

Abstract

As the COVID-19 outbreak has an impact on the global economy, there will be interest in how China's financial markets function during the outbreak. To investigate the path of risk contagion in China's financial sub-markets before and after the COVID-19 outbreak, we divided the 2016-2021 period into two phases. Based on the time of the COVID-19 outbreak, we divided the new stage of economic development into pre-epidemic and post-epidemic stages and employed the DCC-GARCH model to investigate the dynamic correlation coefficients among the financial sub-markets in China. Furthermore, we employed complex network theory and the minimum tree model to describe the risk contagion path between two-stage Chinese financial submarkets. Finally, we provided pertinent recommendations for investors and policymakers and conducted a brief discussion based on the findings of the research.

摘要

由于新冠疫情爆发对全球经济产生影响,人们将关注疫情期间中国金融市场的运行情况。为了研究新冠疫情爆发前后中国金融子市场的风险传染路径,我们将2016 - 2021年这段时间分为两个阶段。基于新冠疫情爆发的时间,我们将经济发展的新阶段分为疫情前和疫情后阶段,并采用DCC - GARCH模型来研究中国金融子市场之间的动态相关系数。此外,我们运用复杂网络理论和最小生成树模型来描述两阶段中国金融子市场之间的风险传染路径。最后,我们为投资者和政策制定者提供了相关建议,并根据研究结果进行了简要讨论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/381a/9407423/56109aa3688d/entropy-24-01120-g001a.jpg

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