Development and Test of an Artificial-Immune- Abnormal-Trading-Detection System for Financial Markets

  • Vincent C. S. Lee
  • Xingjian Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3644)


In this paper, we implement a pilot study on the detection of abnormal financial asset trading activities using an artificial immune system. We develop a prototype artificial immune abnormal-trading-detecting system (AIAS)to scan the proxy data from the stock market and detect the abnormal trading such as insider trading and market manipulation, etc. among them. The rapid and real time detection capability of abnormal trading activities has been tested under simulated stock market as well as using real intraday price data of selected Australian stocks. Finally, three parameters used in the AIAS are tested so that the performance and robustness of the system are enhanced.


Stock Market Artificial Immune System Proxy Data Inside Trading Trading Pattern 
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 2005

Authors and Affiliations

  • Vincent C. S. Lee
    • 1
  • Xingjian Yang
    • 1
  1. 1.School of Business Systems, Faculty of Information TechnologyMonash UniversityAustralia

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