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Crisp vs Fuzzy Decision Support Systems for the Forex Market

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Information Technology, Systems Research, and Computational Physics (ITSRCP 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 945))

Abstract

A new concept of the multicriteria fuzzy trading system using the technical analysis is proposed. The existing trading systems use different indicators of the technical analysis and generate buy or sell signal only when assumed conditions for a given indicator are satisfied. The information presented to the trader – decision maker is binary. The decision maker obtains a signal or no. In comparison to the existing traditional systems called as crisp, the proposed system treats all considered indicators jointly using the multicriteria approach and the binary information is extended with the use of the fuzzy approach. Currency pairs are considered as variants in the multicriteria space in which criteria refer to different technical indicators. The introduced domination relation allows generating the most efficient, non-dominated (Pareto optimal) variants in the space. An algorithm generated these non-dominated variants is proposed. It is implemented in a computer-based system assuring sovereignty of the decision maker.

We compare the proposed system with the traditional crisp trading system. It is made experimentally on different sets of real-world data for three different types of trading: short-term, medium and long-term trading. The achieved results show the computational efficiency of the proposed system. The proposed approach is more robust and flexible than the traditional crisp approach. The set of variants derived for the decision maker in the case of the proposed approach includes only non-dominated variants, what is not possible in the case of the traditional crisp approach.

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Acknowledgments

The preliminary version of this paper was presented at the 3rd Conference on Information Technology, Systems Research and Computational Physics, 2–5 July 2018, Cracow, Poland [10].

Author information

Authors and Affiliations

  1. Faculty of Informatics and Communication, Department of Knowledge Engineering, University of Economics, 1 Maja 50, 40-287, Katowice, Poland

    Przemysław Juszczuk

  2. Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Lech Kruś

Authors
  1. Przemysław Juszczuk
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  2. Lech Kruś
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Corresponding author

Correspondence to Przemysław Juszczuk .

Editor information

Editors and Affiliations

  1. Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland

    Piotr Kulczycki

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. Faculty of Engineering Sciences, Széchenyi István University, Győr, Hungary

    László T. Kóczy

  4. Faculty of Civil Engineering, Slovak University of Technology, Bratislava, Slovakia

    Radko Mesiar

  5. Department of Electronic Systems, Aalborg University, Aalborg, Denmark

    Rafal Wisniewski

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Juszczuk, P., Kruś, L. (2020). Crisp vs Fuzzy Decision Support Systems for the Forex Market. In: Kulczycki, P., Kacprzyk, J., Kóczy, L., Mesiar, R., Wisniewski, R. (eds) Information Technology, Systems Research, and Computational Physics. ITSRCP 2018. Advances in Intelligent Systems and Computing, vol 945. Springer, Cham. https://doi.org/10.1007/978-3-030-18058-4_12

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