基于大数据分析的股市系统性风险演化机理及监控策略研究

本项目以复杂系统与复杂性科学的思想为指导，融合信息论、行为金融学和复杂网络等理论，通过大数据分析对股市中具有不同扩散特征的多元信息、具有多维属性的投资者以及多种类型的股票进行深入挖掘，进而构建更加贴近实际股票市场特征的人工股票市场模型，研究股票市场系统性风险的演化机理，并在此基础上设计股票市场系统性风险监控策略。具体研究内容有：运用大数据分析方法挖掘实际股票市场的多重复杂形态，以此构建人工股票市场模型；分别从多元信息扩散的多层网络、多维属性投资者间交互网络以及由投资者交易形成的股票关联网络角度探讨股票市场系统性风险的演化机理；设计股票市场系统性风险监控策略，分析不同风险监控策略效果。本项目将对股票市场系统性风险的形成机理进行深入研究，具有较强的创新性，其研究成果对我国股票市场系统性风险的防范具有较高的理论意义和应用参考价值。

Directed by the thoughts of complex systems and complex science, especially the theories of information, behavioral finance, complex network and the like, the big data analysis is used to deeply mine the diversified information with different diffusion features, investors with multidimensional properties and polytypic stocks. Then an artificial stock market is constructed to explore the evolution mechanism of systemic risk, and strategies to supervise systemic risk in the stock market. The main research contents are as follows. The multiple complex morphologies of the stock market are analyzed through big data methods to construct the artificial stock market. The evolution mechanism of systemic risk in the stock market is analyzed from the perspectives of the multi-layer network resulted from diversified information diffusion, the interaction network among investors with multidimensional properties and the stock correlation network. Different strategies are designed and compared to supervise systemic risk. This project would conduct an intensive and innovative study on the evolution mechanism of systemic risk in the stock market, and the results would have prominent theoretical and practical values for supervising systemic risk in Chinese stock market.