Suppr超能文献

基于动态复杂网络的中国股票市场系统性风险演化特征

The Evolution Characteristics of Systemic Risk in China's Stock Market Based on a Dynamic Complex Network.

作者信息

Shi Yong, Zheng Yuanchun, Guo Kun, Jin Zhenni, Huang Zili

机构信息

School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100190, China.

Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China.

出版信息

Entropy (Basel). 2020 Jun 2;22(6):614. doi: 10.3390/e22060614.

Abstract

The stock market is a complex system with unpredictable stock price fluctuations. When the positive feedback in the market amplifies, the systemic risk will increase rapidly. During the last 30 years of development, the mechanism and governance system of China's stock market have been constantly improving, but irrational shocks have still appeared suddenly in the last decade, making investment decisions risky. Therefore, based on the daily return of all a-shares in China, this paper constructs a dynamic complex network of individual stocks, and represents the systemic risk of the market using the average weighting degree, as well as the adjusted structural entropy, of the network. In order to eliminate the influence of disturbance factors, empirical mode decomposition (EMD) and grey relational analysis (GRA) are used to decompose and reconstruct the sequences to obtain the evolution trend and periodic fluctuation of systemic risk. The results show that the systemic risk of China's stock market as a whole shows a downward trend, and the periodic fluctuation of systemic risk has a long-term equilibrium relationship with the abnormal fluctuation of the stock market. Further, each rise of systemic risk corresponds to external factor shocks and internal structural problems.

摘要

股票市场是一个复杂的系统,股价波动难以预测。当市场中的正反馈放大时,系统性风险将迅速增加。在过去30年的发展过程中,中国股票市场的机制和治理体系不断完善,但在过去十年中仍突然出现非理性冲击,使得投资决策具有风险。因此,本文基于中国所有A股的日收益率,构建了个股动态复杂网络,并使用网络的平均加权度以及调整后的结构熵来表征市场的系统性风险。为了消除干扰因素的影响,采用经验模态分解(EMD)和灰色关联分析(GRA)对序列进行分解和重构,以获得系统性风险的演变趋势和周期性波动。结果表明,中国股票市场的整体系统性风险呈下降趋势,系统性风险的周期性波动与股票市场的异常波动存在长期均衡关系。此外,系统性风险的每次上升都对应着外部因素冲击和内部结构问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4fa9/7517145/baa98820d250/entropy-22-00614-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验