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Machine Learning Algorithmic Study of the Naira Exchange Rate

Author

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  • Ledisi Giok Kabari

    (Computer Science Department, Ken Saro-Wiwa Polytechnic, Bori, Nigeria)

  • Marcus B. Chigoziri

    (Computer Science Department, Ignatius Ajuru University of Education, Port Harcourt, Nigeria)

  • Joseph Eneotu

    (Computer Science Department, Ignatius Ajuru University of Education, Port Harcourt, Nigeria)

Abstract

In this study, we discuss various machine learning algorithms and architectures suitable for the Nigerian Naira exchange rate forecast. Our analyses were focused on the exchange rates of the British Pounds, US Dollars and the Euro against the Naira. The exchange rate data was sourced from the Central Bank of Nigeria. The performances of the algorithms were evaluated using Mean Squared Error, Root Mean Squared Error, Mean Absolute Error and the coefficient of determination (R-Squared score). Finally, we compared the performances of these algorithms in forecasting the exchange rates.

Suggested Citation

  • Ledisi Giok Kabari & Marcus B. Chigoziri & Joseph Eneotu, 2020. "Machine Learning Algorithmic Study of the Naira Exchange Rate," European Journal of Engineering and Technology Research, European Open Science, vol. 5(2), pages 183-186, February.
    • Handle: RePEc:epw:ejeng0:v:5:y:2020:i:2:id:61739
    DOI: 10.24018/ejeng.2020.5.2.1739
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