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International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2002: Intelligent Data Engineering and Automated Learning — IDEAL 2002 pp 403–409Cite as

Artificial Intelligence in Portfolio Management

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2412))

Abstract

Artificial intelligence supports decision by analyzing enormous information. This paper introduces an intelligent portfolio management system (IPMS) that applies artificial intelligence to assist investors in planning their investments. A prototype is developed based on the portfolio management process, involving stock selection and asset allocation optimization. A genetically optimised fuzzy rule-base is developed for stock selection. Genetic algorithm is used to optimize asset allocation according to investor’s risk aversion.

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References

  1. Dahl Henrik, Meeraus Alexander and Zenios Stavros A. Some Financial Optimization Models: I Risk Management. Financial Optimization. Stavros A. Zenios. Cambridge University Press, 1993.

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Author information

Authors and Affiliations

  1. Department of Computing, The Hong Kong Polytechnic University, Hong Kong

    Man-Chung Chan, Chi-Cheong Wong & W. F. Tse

  2. GERAD and Ecole Polytechique de Montreal, Canada

    Bernard K.-S. Cheung

  3. Dept of Finance and Decision Sciences, Hong Kong Baptist University, Hong Kong

    Gordon Y.-N. Tang

Authors
  1. Man-Chung Chan
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  2. Chi-Cheong Wong
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  3. W. F. Tse
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  4. Bernard K.-S. Cheung
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  5. Gordon Y.-N. Tang
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Electronics, UMIST, Manchester, M60 1QD, UK

    Hujun Yin , Nigel Allinson  & Richard Freeman ,  & 

  2. Department of Computation, UMIST, Manchester, M60 1QD, UK

    John Keane

  3. Department of Biomolecular Science, UMIST, Manchester, M60 1QD, UK

    Simon Hubbard

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© 2002 Springer-Verlag Berlin Heidelberg

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Cite this paper

Chan, MC., Wong, CC., Tse, W.F., Cheung, B.KS., Tang, G.YN. (2002). Artificial Intelligence in Portfolio Management. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_60

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  • DOI: https://doi.org/10.1007/3-540-45675-9_60

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44025-3

  • Online ISBN: 978-3-540-45675-9

  • eBook Packages: Springer Book Archive

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