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Financial Prediction with Neuro-fuzzy Systems

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Artificial Intelligence and Soft Computing – ICAISC 2008 (ICAISC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5097))

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Abstract

An application of neuro-fuzzy systems to supporting trading decisions is presented. The system has the ability to use expert knowledge and to be fitted to the learning data by various machine learning techniques. The proposed approach uses the backpropagation algorithm to determine system parameters on the basis of several indices. Experiments were made on past data showing relatively good performance of the proposed approach.

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Authors and Affiliations

  1. Institute of Mathematics and Computer Science, Jan Długosz University, al. Armii Krajowej 13/15, 42-200, Czȩstochowa, Poland

    Agata Pokropińska

  2. Department of Computer Engineering, Czȩstochowa University of Technology, al. Armii Krajowej 36, 42-200, Czȩstochowa, Poland

    Rafał Scherer

  3. Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Agata Pokropińska & Rafał Scherer

Authors
  1. Agata Pokropińska
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  2. Rafał Scherer
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Editor information

Leszek Rutkowski Ryszard Tadeusiewicz Lotfi A. Zadeh Jacek M. Zurada

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© 2008 Springer-Verlag Berlin Heidelberg

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Pokropińska, A., Scherer, R. (2008). Financial Prediction with Neuro-fuzzy Systems. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_105

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  • DOI: https://doi.org/10.1007/978-3-540-69731-2_105

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69572-1

  • Online ISBN: 978-3-540-69731-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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