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Intraday Analysis of Portfolios on the ASX Using ICA

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Intelligent Data Engineering and Automated Learning (IDEAL 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2690))

Abstract

In this paper we address the problem of forecasting non-gaussian portfolio returns over multiple time scales. We apply a relatively new technique for estimating portfolio returns by considering higher order mutual information. This technique is based on two methodologies: Independent Component Analysis and Gaussian mixtures. We apply this model to intraday data from the ASX. Our findings illustrate that this model is particularly useful in estimating portfolio returns over a short time scale when the distribution is highly non-Gaussian.

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References

  1. Chin, E., Weigend, A., Zimmermann, H.: Computing portfolio risk using Gaussian mixtures and Independent Component Analysis. In: Proceedings of the 1999 IEEE/IAFE/INFORMS, CIFEr 1999, New York, March 1999, pp. 74–117 ( March 1999)

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  2. Hyvarinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, Chichester (2001)

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  3. Kon, S.: Models of Stock Returns – A Comparison. Journal of Finance 39, 147–165

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  4. Lo, K., Coggins, R.: Intraday Analysis of Portfolios on the ASX using ICA, Technical Report, CEL, School of Electrical and Information Engineering, University of Sydney (March 2003)

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Author information

Authors and Affiliations

  1. Computer Engineering Laboratory, Electrical and Information Engineering, University of Sydney, Australia

    Kevin Lo & Richard Coggins

Authors
  1. Kevin Lo
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  2. Richard Coggins
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  2. Department of Computer Science, Hong Kong Baptist University, Hong Kong

    Yiu-ming Cheung

  3. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2003 Springer-Verlag Berlin Heidelberg

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Lo, K., Coggins, R. (2003). Intraday Analysis of Portfolios on the ASX Using ICA. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_133

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  • DOI: https://doi.org/10.1007/978-3-540-45080-1_133

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40550-4

  • Online ISBN: 978-3-540-45080-1

  • eBook Packages: Springer Book Archive

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