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Characteristics of real futures trading networks

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  • Wang, Junjie
  • Zhou, Shuigeng
  • Guan, Jihong

Abstract

Futures trading is the core of futures business, and it is considered as one of the typical complex systems. To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from the Shanghai Futures Exchange to construct futures trading networks, in which nodes are trading participants, and two nodes have a common edge if the two corresponding investors appear simultaneously in at least one trading record as a purchaser and a seller, respectively. Then, we conduct a comprehensive statistical analysis on the constructed futures trading networks. Empirical results show that the futures trading networks exhibit features such as scale-free behavior with interesting odd–even-degree divergence in low-degree regions, small-world effect, hierarchical organization, power-law betweenness distribution, disassortative mixing, and shrinkage of both the average path length and the diameter as network size increases. To the best of our knowledge, this is the first work that uses real data to study futures trading networks, and we argue that the research results can shed light on the nature of real futures business.

Suggested Citation

  • Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:2:p:398-409
    DOI: 10.1016/j.physa.2010.09.027
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    References listed on IDEAS

    as
    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Su, B.B. & Chang, H. & Chen, Y.-Z. & He, D.R., 2007. "A game theory model of urban public traffic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 291-297.
    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    4. S. M.G. Caldeira & T. C. Petit Lobão & R. F.S. Andrade & A. Neme & J. G.V. Miranda, 2006. "The network of concepts in written texts," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 49(4), pages 523-529, February.
    5. S. C. Wang & J. J. Tseng & C. C. Tai & K. H. Lai & W. S. Wu & S. H. Chen & S. P. Li, 2008. "Network topology of an experimental futures exchange," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(1), pages 105-111, March.
    6. Liu, Jian-Guo & Xuan, Zhao-Guo & Dang, Yan-Zhong & Guo, Qiang & Wang, Zhong-Tuo, 2007. "Weighted network properties of Chinese nature science basic research," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 302-314.
    7. Zhou, Shuigeng & Hu, Guobiao & Zhang, Zhongzhi & Guan, Jihong, 2008. "An empirical study of Chinese language networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3039-3047.
    8. Bernardo A. Huberman & Lada A. Adamic, 1999. "Growth dynamics of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 131-131, September.
    9. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    10. Garlaschelli, Diego & Battiston, Stefano & Castri, Maurizio & Servedio, Vito D.P. & Caldarelli, Guido, 2005. "The scale-free topology of market investments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 491-499.
    11. Fu, Feng & Liu, Lianghuan & Wang, Long, 2008. "Empirical analysis of online social networks in the age of Web 2.0," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 675-684.
    12. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    13. Han, Ding-Ding & Qian, Jiang-Hai & Liu, Jin-Gao, 2009. "Network topology and correlation features affiliated with European airline companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(1), pages 71-81.
    14. Raj Kumar Pan & Sitabhra Sinha, 2007. "Collective behavior of stock price movements in an emerging market," Papers 0704.0773, arXiv.org, revised Nov 2007.
    15. J.-P. Onnela & K. Kaski & J. Kertész, 2004. "Clustering and information in correlation based financial networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 353-362, March.
    16. Liu, Jianguo & Dang, Yanzhong & Wang, Zhongtuo, 2006. "Complex network properties of Chinese natural science basic research," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 578-586.
    Full references (including those not matched with items on IDEAS)

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    6. Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Yong-Jie Zhang & W. -X. Zhou, 2012. "Trading networks, abnormal motifs and stock manipulation," Papers 1301.0007, arXiv.org.
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