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中文摘要：
传统的两变量Granger因果分析法容易产生伪因果关系,且不能刻画变量间的同期因果性.利用图模型方法研究多维时间序列变量间Granger因果关系,通过Granger因果图的建立将问题转化为Granger因果图结构的辨识问题,利用局部密度估计法构造相应的辨识统计量,采用bootstrap方法来确定检验统计量的原分布.模拟分析以及对于中国股市间Granger因果关系的研究说明了该方法的有效性.
英文摘要：
Traditional two-variable Granger causality analysis method is prone to inducing spurious causal relationship and cannot portray the immediate causal relationship.This paper explores how to use graphical model methods to analyze the Granger causality graphs among components of multivariate time series.Granger causality graphs of time series is presented and the structural identification problem of Granger causality graph is investigated.A statistic based on local density estimator is proposed,and a bootstrap methods is considered for determining the null distribution of the test statistic.The validity of the proposed method is confirmed by simulations analysis and investigating the Granger causal relationships of the China＇s stock market.
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