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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2018
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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. |
format | Online Article Text |
id | pubmed-5882728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The Royal Society Publishing |
record_format | MEDLINE/PubMed |
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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