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      Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system

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          Abstract

          Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion.

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          Most cited references45

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          Econometric measures of connectedness and systemic risk in the finance and insurance sectors

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            A network perspective of the stock market

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              Complex network analysis of time series

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                Author and article information

                Journal
                R Soc Open Sci
                R Soc Open Sci
                RSOS
                royopensci
                Royal Society Open Science
                The Royal Society Publishing
                2054-5703
                March 2018
                28 March 2018
                28 March 2018
                : 5
                : 3
                : 172092
                Affiliations
                [1 ]School of Humanities and Economic Management, China University of Geosciences , Beijing 100083, People's Republic of China
                [2 ]Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources , Beijing 100083, People's Republic of China
                [3 ]Open Lab of Talents Evaluation, Ministry of Land and Resources , Beijing 100812, People's Republic of China
                Author notes
                Author for correspondence: Xiangyun Gao e-mail: gaoxy@ 123456cugb.edu.cn

                Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.figshare.c.4035215.

                Author information
                http://orcid.org/0000-0003-2101-1609
                Article
                rsos172092
                10.1098/rsos.172092
                5882728
                29657804
                1b0fc86c-9b44-41a5-b8a1-044def8f14b0
                © 2018 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 5 December 2017
                : 26 February 2018
                Funding
                Funded by: Humanities and Social Sciences planning funds project under the Ministry of Education of the PRC;
                Award ID: 17YJCZH047
                Funded by: Fundamental Research Funds for the Central Universities;
                Award ID: 2-9-2015-303
                Funded by: Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources;
                Award ID: CCA2017.11
                Funded by: Beijing Natural Science Foundation;
                Award ID: 9174041
                Categories
                1008
                194
                Computer Science
                Research Article
                Custom metadata
                March, 2018

                complex network,time series,cointegration,granger causality,financial system

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