Network structure detection and analysis of Shanghai stock market

<p><strong>Purpose:</strong> In order to investigate community structure of the component stocks of SSE (Shanghai Stock Exchange) 180-index, a stock correlation network is built to find the intra-community and inter-community relationship.</p> <p><strong>Design/me...

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Main Authors: Sen Wu, Mengjiao Tuo, Deying Xiong
Format: Article
Language:English
Published: OmniaScience 2015-04-01
Series:Journal of Industrial Engineering and Management
Subjects:
Online Access:http://www.jiem.org/index.php/jiem/article/view/1314
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author Sen Wu
Mengjiao Tuo
Deying Xiong
author_facet Sen Wu
Mengjiao Tuo
Deying Xiong
author_sort Sen Wu
collection DOAJ
description <p><strong>Purpose:</strong> In order to investigate community structure of the component stocks of SSE (Shanghai Stock Exchange) 180-index, a stock correlation network is built to find the intra-community and inter-community relationship.</p> <p><strong>Design/methodology/approach:</strong> The stock correlation network is built taking the vertices as stocks and edges as correlation coefficients of logarithm returns of stock price. It is built as undirected weighted at first. GN algorithm is selected to detect community structure after transferring the network into un-weighted with different thresholds.</p> <p><strong>Findings:</strong> The result of the network community structure analysis shows that the stock market has obvious industrial characteristics. Most of the stocks in the same industry or in the same supply chain are assigned to the same community. The correlation of the internal stock prices’ fluctuation is closer than in different communities. The result of community structure detection also reflects correlations among different industries.</p> <p><strong>Originality/value:</strong> Based on the analysis of the community structure in Shanghai stock market, the result reflects some industrial characteristics, which has reference value to relationship among industries or sub-sectors of listed companies.</p>
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spelling doaj.art-01801bb06b364623aad422ce75c25fd72022-12-21T23:59:14ZengOmniaScienceJournal of Industrial Engineering and Management2013-84232013-09532015-04-018238339810.3926/jiem.1314342Network structure detection and analysis of Shanghai stock marketSen Wu0Mengjiao Tuo1Deying Xiong2University of Science and Technology BeijingUniversity of Science and Technology BeijingUniversity of Science and Technology Beijing<p><strong>Purpose:</strong> In order to investigate community structure of the component stocks of SSE (Shanghai Stock Exchange) 180-index, a stock correlation network is built to find the intra-community and inter-community relationship.</p> <p><strong>Design/methodology/approach:</strong> The stock correlation network is built taking the vertices as stocks and edges as correlation coefficients of logarithm returns of stock price. It is built as undirected weighted at first. GN algorithm is selected to detect community structure after transferring the network into un-weighted with different thresholds.</p> <p><strong>Findings:</strong> The result of the network community structure analysis shows that the stock market has obvious industrial characteristics. Most of the stocks in the same industry or in the same supply chain are assigned to the same community. The correlation of the internal stock prices’ fluctuation is closer than in different communities. The result of community structure detection also reflects correlations among different industries.</p> <p><strong>Originality/value:</strong> Based on the analysis of the community structure in Shanghai stock market, the result reflects some industrial characteristics, which has reference value to relationship among industries or sub-sectors of listed companies.</p>http://www.jiem.org/index.php/jiem/article/view/1314complex network, stock market, community structure, GN algorithm
spellingShingle Sen Wu
Mengjiao Tuo
Deying Xiong
Network structure detection and analysis of Shanghai stock market
Journal of Industrial Engineering and Management
complex network, stock market, community structure, GN algorithm
title Network structure detection and analysis of Shanghai stock market
title_full Network structure detection and analysis of Shanghai stock market
title_fullStr Network structure detection and analysis of Shanghai stock market
title_full_unstemmed Network structure detection and analysis of Shanghai stock market
title_short Network structure detection and analysis of Shanghai stock market
title_sort network structure detection and analysis of shanghai stock market
topic complex network, stock market, community structure, GN algorithm
url http://www.jiem.org/index.php/jiem/article/view/1314
work_keys_str_mv AT senwu networkstructuredetectionandanalysisofshanghaistockmarket
AT mengjiaotuo networkstructuredetectionandanalysisofshanghaistockmarket
AT deyingxiong networkstructuredetectionandanalysisofshanghaistockmarket