Network Structure Detection and Analysis of Shanghai Stock Market

被引：4

作者：

Wu, Sen ^{[1
]}

Tuo, Mengjiao ^{[1
]}

Xiong, Deying ^{[1
]}

机构：

[1] Univ Sci & Technol Beijing, Beijing, Peoples R China

来源：

JOURNAL OF INDUSTRIAL ENGINEERING AND MANAGEMENT-JIEM | 2015年 / 8卷 / 02期

基金：

中国国家自然科学基金;

关键词：

complex network; stock market; community structure; GN algorithm;

D O I：

10.3926/jiem.1314

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Purpose: 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. Design/methodology/approach: 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. Findings: 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 stock prices' fluctuation in the internal community is closer than in different ones. The result of community structure detection also reflects correlations among different industries. Originality/value: 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.

引用

页码：383 / 398

页数：16

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[2]

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