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

Vincent Cheng-Siong Lee; Xing Jian Yang

doi:10.1007/11538059_43

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

Vincent Cheng-Siong Lee, Xing Jian Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

5 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005)
Editors	De-Shuang Huang, Xiao-Ping Zhang, Guang-Bin Hunag
Place of Publication	Germany
Publisher	Springer
Pages	410-419
Number of pages	10
Volume	3644
ISBN (Print)	9783540282266
DOIs	https://doi.org/10.1007/11538059_43
Publication status	Published - 2005
Event	International Conference on Intelligent Computing 2005 - Hefei, China Duration: 23 Aug 2005 → 26 Aug 2005 Conference number: 1st https://link.springer.com/book/10.1007/11538059 (Proceedings - Part 1)

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3644 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Intelligent Computing 2005
Abbreviated title	ICIC 2005
Country/Territory	China
City	Hefei
Period	23/08/05 → 26/08/05
Internet address	https://link.springer.com/book/10.1007/11538059 (Proceedings - Part 1)

Keywords

Tral
Volatility

Access to Document

10.1007/11538059_43

Cite this

Lee, V. C.-S., & Yang, X. J. (2005). Development and test of an artificial-immune-abnormal-trading-detection system for financial markets. In D.-S. Huang, X.-P. Zhang, & G.-B. Hunag (Eds.), Proceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005) (Vol. 3644, pp. 410-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3644 LNCS). Springer. https://doi.org/10.1007/11538059_43

Lee, Vincent Cheng-Siong ; Yang, Xing Jian. / Development and test of an artificial-immune-abnormal-trading-detection system for financial markets. Proceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005). editor / De-Shuang Huang ; Xiao-Ping Zhang ; Guang-Bin Hunag. Vol. 3644 Germany : Springer, 2005. pp. 410-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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Lee, VC-S & Yang, XJ 2005, Development and test of an artificial-immune-abnormal-trading-detection system for financial markets. in D-S Huang, X-P Zhang & G-B Hunag (eds), Proceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005). vol. 3644, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3644 LNCS, Springer, Germany, pp. 410-419, International Conference on Intelligent Computing 2005, Hefei, China, 23/08/05. https://doi.org/10.1007/11538059_43

Development and test of an artificial-immune-abnormal-trading-detection system for financial markets. / Lee, Vincent Cheng-Siong; Yang, Xing Jian.
Proceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005). ed. / De-Shuang Huang; Xiao-Ping Zhang; Guang-Bin Hunag. Vol. 3644 Germany: Springer, 2005. p. 410-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3644 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AB - 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.

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Lee VCS, Yang XJ. Development and test of an artificial-immune-abnormal-trading-detection system for financial markets. In Huang DS, Zhang XP, Hunag GB, editors, Proceedings of the International Conference on Intelligent Computing: Advances in Intelligent Computing (ICIC 2005). Vol. 3644. Germany: Springer. 2005. p. 410-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11538059_43

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

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