Abstract
In the work, we present a method to analyze block & comovement effect of stock market by finding out the community structure in the financial complex network. We choose the stocks from Shanghai and Shenzhen 300 Index as data source and convert them into the complex network in matrix format which is based on the measurements of correlation we proposed in this paper. The classical GN algorithm and the NetDraw tool are applied to obtain the modularity and draw all the community structures. The results of our work can offer not only the internal information about the capital flows in the stock market but also the prediction of variation and trend line of some stocks with delay-correlation.
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References
Bonanno, G., Lillo, F., Mantegna, R.N.: Levels of complexity in financial markets, arXiv: cond-mat/0104369 (2001)
Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004)
Pujol, J.M., Bejar, J., Delgado, J.: Clustering algorithm for determining community structure in large networks. Phys. Rev. E 74, 016107 (2006)
Hu, Y., Li, M., Zhang, P., Fan, Y., Di, Z.: Community detection by signaling on complex networks. Phys. Rev. E 78, 016115 (2008)
Due to no formal translated English name for the stock in China, we use its origin Chinese name in Figure but translate it in our analysis and discussion
Newman, M.E.J.: Mixing patterns in networks. Phys. Rev. E 67, 026126 (2003)
Hanneman, R.R.: Introduction to social network methods (2005)
Glover, F.: Tabu Search Part 2. ORSA Journal on Computing 2, 4–32 (1990)
Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., Parisi, D.: Defining and identifying communities in networks. Proc. Natl. Acad. Sci. 101, 2658–2663 (2004)
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© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Du, C., Wang, X., Qiu, L. (2009). Block & Comovement Effect of Stock Market in Financial Complex Network. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_6
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DOI: https://doi.org/10.1007/978-3-642-02469-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02468-9
Online ISBN: 978-3-642-02469-6
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