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| Study on Community Identification of Stock Network Based on Synchronization Theory |
| MA Jinghao, CAI Shimin
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| School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731 |
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Abstract The substructure of stock network, e.g. community, is investigated based on the synchronization theory by utilizing the correlation matrix of time series of stock price fluctuation. Through the spectral analysis on the correlation matrix, it’s determined that the complicated community structure obviously exists in the stock network. Then, the clustering algorithm based on the synchronization theory incorporating with the Kuramoto model is used to dynamically identify the community structure, which suggests that the groups of stocks well agree with the taxonomy of stock market. We also apply the fast community detecting algorithm to verify the former results with respect to the same parametric constrains.
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Received: 31 July 2013
Published: 22 June 2026
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