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

机译:基于动态复杂网络的中国股市系统风险的演变特征

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摘要

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.
机译:股市是一个复杂的系统,具有不可预测的股票价格波动。当市场上积极反馈放大时,系统风险将迅速增加。在过去30年的发展中,中国股市的机制和治理体系一直在不断改进,但在过去十年中,不合理的冲击仍然突然出现,使投资决策危险。因此,根据中国所有A股的每日回报,本文构建了一个动态的个人股票网络,代表了使用平均加权度的市场的系统风险,以及调整后的结构熵网络。为了消除干扰因素的影响,经验模式分解(EMD)和灰色关联分析(GRA)的用于分解和重构的序列,以获得演进趋势和系统性风险周期性波动。结果表明,中国股市的系统性风险作为一个整体呈现下降趋势,且系统性风险的周期性波动与股市的异常波动长期的均衡关系。此外,系统风险的每次上升对应于外部因素冲击和内部结构问题。

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