Development and test of an artificial-immune-abnormal-trading-detection system for financial markets

Vincent Cheng-Siong Lee, Xing Jian Yang

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    5 Citations (Scopus)


    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.

    Original languageEnglish
    Title of host publicationProceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005)
    EditorsDe-Shuang Huang, Xiao-Ping Zhang, Guang-Bin Hunag
    Place of PublicationGermany
    Number of pages10
    ISBN (Print)9783540282266
    Publication statusPublished - 2005
    EventInternational Conference on Intelligent Computing 2005 - Hefei, China
    Duration: 23 Aug 200526 Aug 2005
    Conference number: 1st (Proceedings - Part 1)

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3644 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    ConferenceInternational Conference on Intelligent Computing 2005
    Abbreviated titleICIC 2005
    Internet address


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