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International Conference on Practical Applications of Agents and Multi-Agent Systems

PAAMS 2017: Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems pp 107–116Cite as

Evolving Trading Signals at Foreign Exchange Market

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 722))

Abstract

Paper examines the merit of evolutionary algorithms to generate trading signals for trading decisions at financial markets. We focus on foreign-exchange market. It is among the largest financial markets. “Technical” traders base their decisions on a set of technical rules evolved from past market activity. We employ a genetic algorithm to learn a set of profitable trading rules considering transaction costs; each rule generates a ‘buy’, ‘hold’, or ‘sell’ signal using moving average technical rule. We empirically evaluate our approach using exchange rates of four major currency pairs over the period 2000 to 2015. Performance evaluation on out-of-sample data indicates that our approach is able to provide acceptably high returns on investment. Comparison with exhaustive search proves convincing performance of our approach.

S. Galeshchuk—Fulbright Scholar at Nova Southeastern University, 2015–2016

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Author information

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. Nova Southeastern University, Fort Lauderdale, USA

    Sumitra Mukherjee

Authors
  1. Svitlana Galeshchuk
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  2. Sumitra Mukherjee
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Corresponding author

Correspondence to Svitlana Galeshchuk .

Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Javier Bajo

  2. Polytechnic Institute of Porto, Porto, Portugal

    Zita Vale

  3. University of Southern Denmark, Odense, Denmark

    Kasper Hallenborg

  4. University of Porto, Porto, Portugal

    Ana Paula Rocha

  5. Lille University of Science and Technology, Lille, France

    Philippe Mathieu

  6. Poznan University of Technology, Poznan, Poland

    Pawel Pawlewski

  7. Polytechnic University of Valencia, Valencia, Spain

    Elena Del Val

  8. University of Minho, Braga, Portugal

    Paulo Novais

  9. National Laboratory of Energy and Geology, Lisbon, Portugal

    Fernando Lopes

  10. National University of Colombia, Manizales, Caldas, Colombia

    Nestor D. Duque Méndez

  11. Polytechnic University of Valencia, Valencia, Spain

    Vicente Julián

  12. Malmö University, Malmo, Sweden

    Johan Holmgren

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Galeshchuk, S., Mukherjee, S. (2017). Evolving Trading Signals at Foreign Exchange Market. In: Bajo, J., et al. Highlights of Practical Applications of Cyber-Physical Multi-Agent Systems. PAAMS 2017. Communications in Computer and Information Science, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-60285-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-60285-1_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60284-4

  • Online ISBN: 978-3-319-60285-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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