Detecting Environmental Changes through High-Resolution Data of Financial Markets

  • Aki-Hiro Sato
Part of the Studies in Computational Intelligence book series (SCI, volume 199)


This article proposes methods to detect states of financial markets both comprehensively and with a high-resolution. In order to quantify trading patterns several mathematical methods are proposed based on frequencies of quotations/ transactions estimated from high-resolution data of financial markets. The empirical results (graphical network representation and quantification of states of market participants) for the foreign exchange market are shown. It is concluded that synchronous behavior associated with a large population of market participants may be a candidate of precursory signs leading to an environmental change.


Bipartite Graph Market Participant Physical Review Letter Foreign Exchange Market Synchronous State 
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 2009

Authors and Affiliations

  • Aki-Hiro Sato
    • 1
  1. 1.Department of Applied Mathematics and Physics, Graduate School of InformaticsKyoto University 

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