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Impact of ELM Parameters and Investment Horizon for Currency Exchange Prediction

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Artificial Intelligence and Soft Computing (ICAISC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12854))

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Abstract

The foreign exchange market is of the utmost importance for many sectors of the economy, therefore attempts to forecast changes in currency price levels are the research area of many practitioners and theorists. The article aims at examining the impact of settings of various neural network parameters on the results of currency forecasts. The three currency pairs the US dollar, British pound, and Swiss franc to EUR were selected for the analysis. The forecast results for different network settings are examined with three different indicators: forecast error, the ratio of correctly forecasted changes in the course direction and the potential profit generated. The neural network used for the study is Extreme Learning Machine and the forecast horizons taken into account are in the range of one to ten days. The better-quality forecasts based on price levels than on rates of return was shown and good quality forecasts for two out of three currency pairs was obtained in the study. The article also presents the relationship between the results generated by the neural network and the settings of these networks - in particular, the impact of the number of delays on forecast errors and the number of hidden nodes on all three assessment parameters.

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Authors and Affiliations

  1. Poznan University of Economics and Business, Poznan, Poland

    Jakub Morkowski

Authors
  1. Jakub Morkowski
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Correspondence to Jakub Morkowski .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Morkowski, J. (2021). Impact of ELM Parameters and Investment Horizon for Currency Exchange Prediction. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12854. Springer, Cham. https://doi.org/10.1007/978-3-030-87986-0_12

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  • DOI: https://doi.org/10.1007/978-3-030-87986-0_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87985-3

  • Online ISBN: 978-3-030-87986-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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