我国股市网络稳定性及其宏观影响因素——基于三种网络拓扑结构、鲁棒性的实证研究

基于金融时间序列的多重分形特征及衡量市场风险的VaR模型,建立我国沪深股市的股票关联网络,实证研究三种网络拓扑结构特征,并使用协整检验方法分析网络稳定性和宏观经济变量间的长期均衡关系。结果表明:股票价格网络不具有无标度性,多标度网络和风险网络都具有无标度性;在三种网络中,风险网络具有更强的鲁棒性。此外,股市波动率和网络稳定系数间互为格兰杰因果关系,股市波动的前期变化能有效解释网络稳定性系数的变化;网络稳定性与宏观经济变量间具有长期的均衡关系,GDP增长率、消费者物价水平CPI对网络稳定性具有正向效应,利率对网络稳定性具有负向效应。风险网络的提出有助于分析我国股市的短期风险及稳定性,并为制定系统风险防御策略提供参考。

The Stability of China Stock Market Network and Its Macroeconomic Factors ——An Empirical Study Based on Three Network Topologies and Robustness

Based on the multifractal characteristics of financial time series and the VaR model of measuring market risk, this paper constructs China's stock market networks and studies empirically three networks' topological features. Then through cointegration method, we analyze the long-term equilibrium relationship between network stability and macroeconomic variables. The results show that: the stock price network does not have scale-free features, while the multi-scale network and the risk network have scale-free features. Among three types of networks, the risk network is the most robust. Additionally, the stock market volatility and the network stability coefficient are Granger causality, and the early changes of the stock market volatility can effectively explain the changes of network stability coefficient. There is a long-term equilibrium relationship between network stability and macroeconomic variables. GDP growth rate and CPI have a positive effect on network stability, and the interest rate has a negative effect on network stability. The risk network provides a reference for analyzing the short-erm risk and stability of China's stock market, as well as formulating a defense strategy about system risk.