使用2015年1月到2018年12月期间东方财富网45家上市 金融机构1000万余条发帖信息为研究载体, 从网络关注度和网络情绪两个角度构建``网络关注度''、``网络 情绪''和``网络意见分歧''共3个网络舆情指数; 然后使用DCC-GARCH模型估计CoVaR度量系统 性金融风险指标; 之后采用系统广义矩估计(SGMM)和差分广义矩估计(DGMM)方法实证分析 了网络舆情对系统性金融风险的影响效应. 研究发现: 网络关注度对系统性金 融风险具有显著影响, 投资者网络关注度越高, 系统性金融风险水平越高; 网络情绪对系统性金融风险的影响具有非对称性, 并且网络积极情绪较之消极情绪 对系统性金融风险的影响更大; 另外, 网络意见分歧越大, 系统性金融风险水平 越高. 文章研究表明, 基于``互联网+风险管理''对系统性金融风险的防范和化解具有重要的理论及现实意义.

This paper uses more than 12 million posts from 45 listed financial institutions in eastmoney.com from January 2015 to December 2018 as the research carrier, inthepurposeofconstructingthree network public opinion indexes: ``Network Attention", ``Network Emotion" and ``Network Opinion Divergence" from two perspectives of network attention and network emotion. Then DCC-GARCH model will be used to estimate CoVaR as the systemic financial risk index. Meanwhile, SGMM and DGMM methods are employed to analyze the impact of network public opinion on systemic financial risk. The results show that network attention has a significant impact on systemic financial risk, the higher the investor's network attention, the higher the level of systemic financial risk. The influence of network emotion on systemic financial risk is in the nature of asymmetry that the positive emotion has a greater impact than the negative one. In addition, we can see that the greater the divergence of different network opinions is, the higher the level of systemic financial risk is. The research also shows that the combination of Internet study and risk management has theoretical and practical significance to prevent and resolve systemic financial risks.