基于复杂网络的行业动态演化与证券市场风险相关性研究——来自2007—2019年28个行业数据的证据

管理评论 ›› 2021, Vol. 33 ›› Issue (3): 29-40.

基于复杂网络的行业动态演化与证券市场风险相关性研究——来自2007—2019年28个行业数据的证据

刘超^1,2, 钱存¹, 罗春燕¹

1. 北京工业大学经济与管理学院, 北京 100124;
2. 北京现代制造业发展研究基地, 北京 100124

收稿日期:2020-07-16 出版日期:2021-03-28 发布日期:2021-04-06
通讯作者: 刘超(通讯作者),北京工业大学经济与管理学院教授,博士生导师,博士
作者简介:钱存,北京工业大学经济与管理学院硕士研究生;罗春燕,北京工业大学经济与管理学院经济师,硕士。
基金资助:
国家自然科学基金面上项目（62073007；61773029；61273230）；北京市属高校高水平教师队伍建设支持计划长城学者培养计划资助项目（CIT&TCD20170304）。

Research on the Correlation between Industry Dynamic Evolution and Securities Market Risk Based on Complex Network

Liu Chao^1,2, Qian Cun¹, Luo Chunyan¹

1. School of Economics and Management, Beijing University of Technology, Beijing 100124;
2. Modern Manufacturing Industry Development Research Base of Beijing, Beijing 100124

Received:2020-07-16 Online:2021-03-28 Published:2021-04-06

摘要/Abstract

摘要： 证券系统是金融系统的重要组成部分，探究我国上市公司行业关联动态演化与证券市场风险之间的相互关系有重要的理论与实践价值。本文使用互信息系数建立了我国上市公司行业关联网络，采用CAViaR模型对我国证券市场风险进行测度，结合DCCA系数法、非线性Granger因果检验分析网络相关性、分布结构与市场风险间的交互关系，并通过比较两个风险聚集区域的网络特征，深入分析市场风险变化给行业带来的关联与结构变动。研究结果表明：当证券市场风险增大时会促使上市公司行业系统的关联性更强，各个行业表现出较为相似的市场走势，此时系统结构虽更趋近于紧密的“中心-外围”式结构，但上市公司行业系统的自主调节功能会削弱甚至化解市场风险对行业关联形态的影响；行业关联结构的外部形态特征存在周期性的震荡；当行业间的关联性增强时，会在一定程度上加速风险的蔓延和传染。根据上述结论，本文提出了相应的政策建议。

关键词: 相关性, 复杂网络, 网络结构, 市场风险, 互信息系数

Abstract: The securities system is an important part of the financial system. It is of great theoretical and practical value to explore the relationship between the dynamic evolution of industry association of listed companies and the risk of securities market. This paper uses mutual information coefficient to establish the industry correlation network of China's listed companies, uses CAViaR model to measure the risk of China's securities market, and analyzes the network correlation, distribution structure and market wind combined with DCCA coefficient method and nonlinear Granger Causality test. Finally, the network characteristics of the two risk aggregation regions are compared and analyzed. The results show that:when the security market risk increases, the industry system of listed companies will be more related, and each industry will show a similar market trend. At this time, although the system structure tends to be closer to the “center-periphery” structure, the self-regulation function of the industry system of listed companies will weaken or even dissolve the impact of market risk on the industry association and the external morphological characteristics of the association structure have periodic shocks; when the correlation between industries is enhanced, it will accelerate the spread of risks to a certain extent. According to the above conclusions, this paper puts forward the relevant policy recommendations.

Key words: correlation, complex network, network structure, market risk, mutual information coefficient

刘超, 钱存, 罗春燕. 基于复杂网络的行业动态演化与证券市场风险相关性研究——来自2007—2019年28个行业数据的证据[J]. 管理评论, 2021, 33(3): 29-40.

Liu Chao, Qian Cun, Luo Chunyan. Research on the Correlation between Industry Dynamic Evolution and Securities Market Risk Based on Complex Network[J]. Management Review, 2021, 33(3): 29-40.

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