Scale-Free Networks Emerged in the Markets: Human Traders versus Zero-Intelligence Traders

  • Jie-Jun Tseng
  • Shu-Heng Chen
  • Sun-Chong Wang
  • Sai-Ping Li
Conference paper
Part of the Springer Series on Agent Based Social Systems book series (ABSS, volume 6)


We design a Web-based prediction market platform to monitor the trading behavior among the human traders in real-time. Two experiments tied to the outcomes of mayoral election in Taiwan are performed in parallel for 30 days. From the accumulated transaction data, we reconstruct the so-called cash-flow networks. We observe that the network structure is hierarchical and scale-free with a power-law exponent of 1.15±0.07. Through carrying out a post-simulation, we also demonstrate that a simple double auction market with “zero intelligence” traders is capable of generating hierarchical and scale-free networks.


Degree Distribution Limit Order Future Contract Prediction Market Trading Behavior 
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Copyright information

© Springer 2009

Authors and Affiliations

  • Jie-Jun Tseng
    • 1
  • Shu-Heng Chen
    • 2
  • Sun-Chong Wang
    • 3
  • Sai-Ping Li
    • 4
  1. 1.Institute of PhysicsAcademia SinicaTaipeiTaiwan
  2. 2.AI-Econ Research Center and Department of EconomicsNational Chengchi UniversityTaipeiTaiwan
  3. 3.Institute of Systems Biology and BioinformaticsNational Central UniversityChungliTaiwan
  4. 4.Institute of PhysicsAcademia SinicaTaipeiTaiwan

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