Network structure detection and analysis of Shanghai stock market
Abstract: 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 the internal stock prices’ fluctuation is closer
than in different communities. 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.
Author: Sen Wu, Mengjiao Tuo,
Deying Xiong
Journal Code: jptindustrigg150032
