Microstructure Dynamics and Agent-Based Financial Markets

  • Shu-Heng Chen
  • Michael Kampouridis
  • Edward Tsang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6532)


One of the essential features of the agent-based financial models is to show how price dynamics is affected by the evolving microstructure. Empirical work on this microstructure dynamics is, however, built upon highly simplified and unrealistic behavioral models of financial agents. Using genetic programming as a rule-inference engine and self-organizing maps as a clustering machine, we are able to reconstruct the possible underlying microstructure dynamics corresponding to the underlying asset. In light of the agent-based financial models, we further examine the microstructure both in terms of its short-term dynamics and long-term distribution. The time series of the TAIEX is employed as an illustration of the implementation of the idea.


Genetic Programming Trading Rule Behavioral Rule Market Timing Dominant Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Shu-Heng Chen
    • 1
  • Michael Kampouridis
    • 2
  • Edward Tsang
    • 2
  1. 1.AI-ECON Research Center, Department of EconomicsNational Chengchi UniversityTaiwan
  2. 2.School of Computer Science and Electronic EngineeringUniversity of EssexUK

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