Association Journal of CSIAM
Supervised by Ministry of Education of PRC
Sponsored by Xi'an Jiaotong University
ISSN 1005-3085  CN 61-1269/O1

Chinese Journal of Engineering Mathematics ›› 2016, Vol. 33 ›› Issue (3): 270-278.doi: 10.3969/j.issn.1005-3085.2016.03.005

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Granger Causality Detecting Based on Graphical Modelling

WEI Yue-song   

  1. School of Mathematical Science, Huaibei Normal University, Huaibei, Anhui 235000
  • Received:2015-09-14 Accepted:2016-03-21 Online:2016-06-15 Published:2016-08-15
  • Supported by:
    The National Natural Science Foundation of China (61201323); the Natural Science Foundation of Anhui Higher Education Institutions of China (KJ2015A035).

Abstract:

The Granger causality is an important criterion for measuring the dynamic relationship among system variables. In this paper, we apply the graphical model method to explore the Granger causal relations among variables. The Granger causality graph is established and its structural identification is investigated based on the conditional mutual information and permutation test. The test statistics is estimated using the correlation integral of chaos theory and its limiting distribution is proved. Finally, the Granger causality among main international stock markets is investigated using the proposed method.

Key words: Granger causality graphs, conditional mutual information, limiting distribution, correlation integral

CLC Number: