东北大学学报:自然科学版 ›› 2020, Vol. 41 ›› Issue (10): 1500-1508.DOI: 10.12068/j.issn.1005-3026.2020.10.020

• 管理科学 • 上一篇    下一篇

极端行情下中国股市社团结构及系统性风险分析

李延双, 庄新田, 王健, 张伟平   

  1. (东北大学 工商管理学院, 辽宁 沈阳110169)
  • 收稿日期:2019-10-24 修回日期:2019-10-24 出版日期:2020-10-15 发布日期:2020-10-20
  • 通讯作者: 李延双
  • 作者简介:李延双(1993-),男,辽宁营口人,东北大学博士研究生; 庄新田(1956-),男,吉林四平人,东北大学教授,博士生导师; 王健(1980-),女,河北唐山人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(71671030,71571038,71971048).

Analysis of Community Structures and Systemic Risks in China’s Stock Market Under Extreme Conditions

LI Yan-shuang, ZHUANG Xin-tian, WANG Jian, ZHANG Wei-ping   

  1. School of Business Administration, Northeastern University, Shenyang 110169, China.
  • Received:2019-10-24 Revised:2019-10-24 Online:2020-10-15 Published:2020-10-20
  • Contact: ZHUANG Xin-tian
  • About author:-
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摘要: 以2008,2015年国内两次股灾为背景,分别构建股灾前、中、后的中国股市网络社团结构.基于网络中心性构建节点系统重要性及股市系统性风险指标,分析各时期网络社团内核心股票、行业、股票组合及其变化,探究系统性风险与网络拓扑指标、宏观经济指标的相关性.结果表明:股灾期间,工业板块受挫严重,原材料、金融地产、医药卫生板块发挥护盘及修复股指的作用;发现3种特殊的社团结构及部分社团间出现相互融合的趋势;在股指极端波动时期,中国股市系统性风险与部分网络拓扑指标及宏观经济指标具有显著相关性.

关键词: 复杂网络, 网络中心性, 社团结构 , 股灾, 系统性风险

Abstract: Two domestic stock market disasters in 2008 and 2015 were selected as the background to construct China’s stock market network community structures before, during and after the disasters. The node systemic importance index and the systemic risk index of stock market were constructed to analyze the core stocks, industries, stock portfolios and their changes within the network communities in each period, and to explore the correlation between systemic risks and network topological indicators and macroeconomic indicators. The results showed that the industrial sector suffer severe setbacks, and the raw materials, financial real estates, medical and health sectors play a role in protecting the market and repairing stock indexes during the stock market disasters. Three kinds of special community structures are found and some of them have a tendency to merge with each other. During the periods of extreme stock index fluctuations, the systemic risk of China’s stock market is significantly correlated with some network topological indicators and macroeconomic indicators.

Key words: complex network, network centrality, community structure, stock market disaster, systemic risk

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