Research On Causality Analysis Based On Granger Method And Convergent Cross Mapping Method

Causal analysis is a connection between things that goes beyond correlation analysis,more like the internal laws between things.It has been widely used in the fields of neuroscience,economics,climatology,physics,and biology,etc.At present,the mainstream causal analysis method is Granger causality analysis,which is an analysis method based on autoregressive models,which is mostly used for detection Causality of linear systems.In recent years,a new method of causality analysis,the Convergent Cross Mapping(CCM)method,has also been widely used.It is an analysis method based on manifold reconstruction in geometry.In constrast to Granger method,the theoretical structure is not perfect,but it performs better in detecting the causality of non-linear systems.This dissertation mainly explores the reliability of these two causal analysis reasoning,and targets 10 industries.The index conducts causal network analysis,and conducts relevant empirical analysis on the exchange rate and Shanghai Stock Index to analysis the relationship between the exchange rate market and the stock market.This dissertation mainly deal with Granger causality analysis and convergence cross-mapping causality analysis:· It is proposed to use dynamic time warping(DTW)similarity to replace the Euclidean distance and Pearson correlation involved in the cross-convergence mapping algorithm.· A coupled system with one-way causality is constructed to verify the rationality of the Granger causality method and the convergent cross-mapping causality method.Further more,the effects of sampling interval on Granger causality and convergence cross-mapping causality were explored respectively.· Finally,Granger causality is used to carry on network analysis between 10 industries,and the relationship between the exchange rate market and the stock market is explored based on Granger causality analysis and convergence cross-mapping causality analysis.