Advertisement

The Network Topology of the Chinese Creditees

  • Yingli WangEmail author
  • Mingmin Yang
  • Xiangyin Chen
  • Changli Zhou
  • Xiaoguang YangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 660)

Abstract

We provide an empirical analysis of network structure of the Chinese creditee market based on a unique data set from the China Banking Regulatory Commission (CBRC). The data set includes guarantee and shareholding relationships among customers of the top 19 commercial banks in China. With these data, we construct three creditee linkage networks: guarantee network, shareholding network and mixed network. Then we employ complex network measures to extract topological characteristics of the three creditee networks. We find that out-degree and in-degree distributions of the three networks are power law and exponential, respectively. In addition, in the three creditee networks, distributions of component size fit power law. Finally, compared with other real networks (such as networks of Facebook, Google+, Twitter, Citation, Paper cooperation, Web link), the average clustering coefficient, connectivity and density of creditee networks are smaller.

Keywords

Complex networks Creditee networks Topological characteristic 

Notes

Acknowledgments

This research is supported by the National Natural Science Foundation of China under grant number of 71532013.

References

  1. 1.
    Allen, F., Babus, A.: Networks in Finance. In: Kleindorfer, P., Wind, Y., Gunther, R. (eds.) The Network Challenge: Ctrategy, Profit, and Risk in an Interlinked World, p. 367. Prentice Hall Professional, New York (2009)Google Scholar
  2. 2.
    Battiston, S., Caldarelli, G., Georg, C., et al.: Complex derivatives. Nature Phys. 9(3), 123–125 (2013)CrossRefGoogle Scholar
  3. 3.
    Battiston, S., Catanzaro, M.: Statistical properties of corporate board and director networks. Eur. Phys. J. B-Condens. Matter Complex Syst. 38(2), 345–352 (2004)CrossRefGoogle Scholar
  4. 4.
    Bonanno, G., Caldarelli, G., Lillo, F., Mantegna, R.N.: Topology of correlation-based minimal spanning trees in real and model markets. Phys. Rev. E 68(4), 046130 (2003)CrossRefGoogle Scholar
  5. 5.
    Boss, M., Elsinger, H., Summer, M., et al.: Network topology of the interbank market. Quant. Finan. 4(6), 677–684 (2004)CrossRefGoogle Scholar
  6. 6.
    Delpini, D., Battiston, S., Riccaboni, M., et al.: Evolution of Controllability in Interbank Networks. Sci. Rep. 3 (2013)Google Scholar
  7. 7.
    Goyal, S.: Connections: An Introduction to the Economics of Networks. Princeton University Press, Princeton (2012)CrossRefGoogle Scholar
  8. 8.
    Iori, G., Masi, G.D., Precup, O.V., et al.: A network analysis of the Italian overnight money market. J. Econ. Dyn. control 32(1), 259–278 (2008)CrossRefzbMATHGoogle Scholar
  9. 9.
    Jackson, M.O.: Social and Economic Networks. Princeton University Press, Princeton (2010)zbMATHGoogle Scholar
  10. 10.
    Minoiu, C., Reyes, J.A.: Network Analysis of Global Banking: 1978–2009. International Monetary Fund, Washington (2011)Google Scholar
  11. 11.
    Saito, Y.U., Watanabe, T., Iwamura, M.: Do larger firms have more interfirm relationships? Phys. A Stat. Mech. Appl. 383(1), 158–163 (2007)CrossRefGoogle Scholar
  12. 12.
    Souma, W., Fujiwara, Y., Aoyama, H.: Heterogeneous economic networks. In: Namatame, A., Kaizouji, T., Aruka, Y. (eds.) The Complex Networks of Economic Interactions. Lecture Notes in Economics and Mathematical Systems, vol. 567, pp. 79–92. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Vitali, S., Battiston, S.: Geography versus topology in the European ownership network. New J. Phys. 13(6), 063021 (2011)CrossRefGoogle Scholar
  14. 14.
    Vitali, S., Glattfelder, J.B., Battiston, S.: The network of global corporate control. PloS One 6(10), e25995 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2016

Authors and Affiliations

  1. 1.Academy of Mathematics and Systems Science, UCASBeijingChina

Personalised recommendations