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Network topology of an experimental futures exchange

Author

Listed:
  • S. C. Wang
  • J. J. Tseng
  • C. C. Tai
  • K. H. Lai
  • W. S. Wu
  • S. H. Chen
  • S. P. Li

Abstract

Many systems of different nature exhibit scale free behaviors. Economic systems with power law distribution in the wealth are one of the examples. To better understand the working behind the complexity, we undertook an experiment recording the interactions between market participants. A Web server was setup to administer the exchange of futures contracts whose liquidation prices were coupled to event outcomes. After free registration, participants started trading to compete for the money prizes upon maturity of the futures contracts at the end of the experiment. The evolving `cash' flow network was reconstructed from the transactions between players. We show that the network topology is hierarchical, disassortative and small-world with a power law exponent of 1.02±0.09 in the degree distribution after an exponential decay correction. The small-world property emerged early in the experiment while the number of participants was still small. We also show power law-like distributions of the net incomes and inter-transaction time intervals. Big winners and losers are associated with high degree, high betweenness centrality, low clustering coefficient and low degree-correlation. We identify communities in the network as groups of the like-minded. The distribution of the community sizes is shown to be power-law distributed with an exponent of 1.19±0.16. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2008

Suggested Citation

  • 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.
    • Handle: RePEc:spr:eurphb:v:62:y:2008:i:1:p:105-111
    DOI: 10.1140/epjb/e2008-00119-8
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    Cited by:

    1. 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.
    2. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
    3. Aura Reggiani, 2022. "The Architecture of Connectivity: A Key to Network Vulnerability, Complexity and Resilience," Networks and Spatial Economics, Springer, vol. 22(3), pages 415-437, September.
    4. Peng, Dan & Han, Xiao-Pu & Wei, Zong-Wen & Wang, Bing-Hong, 2015. "Punctuated equilibrium dynamics in human communications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 36-44.
    5. 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.
    6. Zhou, Bin & Xie, Jia-Rong & Yan, Xiao-Yong & Wang, Nianxin & Wang, Bing-Hong, 2017. "A model of task-deletion mechanism based on the priority queueing system of Barabási," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 415-421.
    7. Tseng, Jie-Jun & Lin, Chih-Hao & Lin, Chih-Ting & Wang, Sun-Chong & Li, Sai-Ping, 2010. "Statistical properties of agent-based models in markets with continuous double auction mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1699-1707.
    8. Junjie Wang & Shuigeng Zhou & Jihong Guan, 2010. "Characteristics of Real Futures Trading Networks," Papers 1004.4402, arXiv.org, revised Feb 2011.

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