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FOREX Trading Strategy Optimization

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Decision Economics: In the Tradition of Herbert A. Simon's Heritage (DCAI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 618))

Abstract

Developing robust trading rules for forex trading remains a significant challenge for both academics and practitioners. We employ a genetic algorithm to evolve a diverse set of profitable trading rules based on weighted moving average method. We use the daily closing rates between four pairs of currencies – EUR/USD, GBP/USD, USD/JPY, USD/CHF – to develop and evaluate our method. Results are presented for all four currency pairs over the 16 years from 2000 to 2015. Developed approach yields acceptably high returns on out-of-sample data. The rules obtained using our genetic algorithm result in significantly higher returns than those produced by rules identified through exhaustive search.

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Authors and Affiliations

  1. Faculty of Accounting and Audit, Ternopil National Economic University, Ternopil, Ukraine

    Svitlana Galeshchuk

  2. Laboratoire d’Informatique de Grenoble, Université Grenoble Alpes, Grenoble, France

    Svitlana Galeshchuk

  3. College of Engineering and Computing, Nova Southeastern University, Fort Lauderdale, USA

    Sumitra Mukherjee

Authors
  1. Svitlana Galeshchuk
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  2. Sumitra Mukherjee
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Correspondence to Svitlana Galeshchuk .

Editor information

Editors and Affiliations

  1. Department of Philosophical, Pedagogical, and Economic-Quantitative Sciences, Section of Economics and Quantitative Methods, University of Chieti-Pescara, Pescara, Italy

    Edgardo Bucciarelli

  2. Department of Economics, National Chengchi University, Taipei, Taiwan

    Shu-Heng Chen

  3. Departamento de Informática y Automática, Universidad de Salamanca, Salamanca, Spain

    Juan M. Corchado

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Galeshchuk, S., Mukherjee, S. (2018). FOREX Trading Strategy Optimization. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics: In the Tradition of Herbert A. Simon's Heritage. DCAI 2017. Advances in Intelligent Systems and Computing, vol 618. Springer, Cham. https://doi.org/10.1007/978-3-319-60882-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-60882-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60881-5

  • Online ISBN: 978-3-319-60882-2

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