Advertisement

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)

Abstract

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.

Keywords

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    De Castro, L.N., Von Zuben, F.J.: Artificial Immune Systems: Part I – Basic Theory And Applications. Springer, Heidelberg (1999)Google Scholar
  2. 2.
    Anon, Asthma, Allergy: Glossary. CelebrateLove.com owned and operated by James Larry & CelebrateLove.com (accessed October) (2004), available from: http://www.celebratelove.com/asthmaglossary.htm
  3. 3.
    Dasgupta, D.: Artificial Immune Systems and Their Applications. Springer, Heidelberg (1998)Google Scholar
  4. 4.
    Timmis, J., Bentley, P., Hart, E.: Artificial Immune Systems. In: Proceedings of Second International Conference, ICARIS 2003, Edinburgh, UK (September 2003)Google Scholar
  5. 5.
    Anon: Noise [Glossary online], IT Locus.com owned and operated by IT Locus (accessed September) (2004), available from: http://itlocus.com/glossary/noise.html
  6. 6.
    Black, F.: Noise. Journal of Finance 41(3), 530–531 (1985)Google Scholar
  7. 7.
    Gregoire, P., Huangi, H.: Insider Trading. Noise Trading and the Cost of Equity, 4 (2001)Google Scholar
  8. 8.
    Aitken, M., Siow, A.: Improving the Effectiveness of the Surveillance Function in Securities Markets. Working paper. Department of Finance. University of Sydney, Sydney (2003)Google Scholar
  9. 9.
    Anon: Issue 4 – The Importance of Benchmark Creation [Database online]. smarts.com owned and operated by SMARTS Limited (2004), available from: http://www.smarts.com.au/discovery/09d_Discovery4.html (accessed August 2004)
  10. 10.
    Anon: Access to software tools [Library online]. smarts.com owned and operated by SMARTS Limited (accessed August) (2004), available from: http://www.smarts.com.au/new/library/issue.asp
  11. 11.
    Wilmott, P.: Derivatives – The theory and practice of financial engineering. John Wiley & Sons Ltd., Chichester (1998)Google Scholar
  12. 12.
    Anon: Archive of Corporate Law Bulletins of Melbourne University. Owned and operated by Centre for Corporate Law and Securities Regulation, Faculty of Law, The University of Melbourne (accessed February) (2005), available from: http://cclsr.law.unimelb.edu.au/bulletins/archive/Bulletin0052.htm

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

Personalised recommendations