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

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...

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Autores principales: Gao, Xiangyun, Huang, Shupei, Sun, Xiaoqi, Hao, Xiaoqing, An, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882728/
https://www.ncbi.nlm.nih.gov/pubmed/29657804
http://dx.doi.org/10.1098/rsos.172092
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author Gao, Xiangyun
Huang, Shupei
Sun, Xiaoqi
Hao, Xiaoqing
An, Feng
author_facet Gao, Xiangyun
Huang, Shupei
Sun, Xiaoqi
Hao, Xiaoqing
An, Feng
author_sort Gao, Xiangyun
collection PubMed
description 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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spelling pubmed-58827282018-04-13 Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system Gao, Xiangyun Huang, Shupei Sun, Xiaoqi Hao, Xiaoqing An, Feng R Soc Open Sci Computer Science 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. The Royal Society Publishing 2018-03-28 /pmc/articles/PMC5882728/ /pubmed/29657804 http://dx.doi.org/10.1098/rsos.172092 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ 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.
spellingShingle Computer Science
Gao, Xiangyun
Huang, Shupei
Sun, Xiaoqi
Hao, Xiaoqing
An, Feng
Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system
title Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system
title_full Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system
title_fullStr Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system
title_full_unstemmed Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system
title_short Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system
title_sort modelling cointegration and granger causality network to detect long-term equilibrium and diffusion paths in the financial system
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882728/
https://www.ncbi.nlm.nih.gov/pubmed/29657804
http://dx.doi.org/10.1098/rsos.172092
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