格兰杰因果图模型及其在股市信息传导中的应用  

Granger Causality Graphs with Application to Information Transmission in International Stock Markets

作　　者：蔡风景[1,2] 崔玉峰 李元[4] 

机构地区：[1]温州大学数学与信息科学学院,浙江温州325035 [2]数学与交叉科学省普通高校重点实验室(广州大学),广东广州510006 [3]山东省菏泽工业学校,山东菏泽274000 [4]广州大学数学与信息科学学院,广东广州510006

出　　处：《数理统计与管理》2014年第4期744-751,共8页Journal of Applied Statistics and Management

基　　金：国家自然科学基金项目(10971042);教育部人文社科基金青年项目(12YJCZHO02);"数学与交叉科学广东普通高校重点实验室"开放课题资助课题(2012-02-03-01);高等学校博士学科点专项科研基金(20124410110002);国家统计科研计划一般项目(2013LY136)

摘　　要：利用格兰杰因果图表示多维时间序列变量间的因果关系,图中的点表示时间序列分量的点过程,图中的有向边反映序列间的格兰杰因果关系,无向边表示即期因果关系。利用部分定向相干技术研究了格兰杰因果图结构的识别问题,数值模拟表明该方法是有效的。将格兰杰因果图及识别方法应用于国际股票市场分析主要股指的信息流动,结果表明美国和香港股市在信息传导中起着重要作用,中国与国际主要股票市场的直接信息传导较弱,国际股市在信息流动中存在一定的区域效应。The causal relations among components of multivariate time are expressed by Granger causality graph. The vertices, representing the components of the time series, are connected by directed edges according to the Granger causality relations between the variables whereas undirected edges correspond to contemporaneous dependence. The structure identification of Granger causality graph is proposed based on partial directed coherence. The validity of the proposed method is confirmed by simulations. At last, the method is applied to the detection of information transmission in major international financial market. Empirical results show that there is the strong connection between US, HK and other stock markets, Chinese stock market is weekly connected among the major international markets. The Regional segmentation of the major international financial markets is proved in this study.

关 键 词：格兰杰因果图 部分定向相干技术 股票市场 

分 类 号：F830.9[经济管理—金融学] O212[理学—概率论与数理统计]