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Exchange Rate Forecasting with Advanced Machine Learning Methods

Author

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  • Jonathan Felix Pfahler

    (Department of Statistics, University of Augsburg, Universitaetstr. 16, D-86159 Augsburg, Germany)

Abstract

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and XGBoost models. Most approaches show significant and substantial predictive power in directional forecasts. Moreover, the evidence suggests that information regarding prediction timing is a key component in the forecasting performance.

Suggested Citation

  • Jonathan Felix Pfahler, 2021. "Exchange Rate Forecasting with Advanced Machine Learning Methods," JRFM, MDPI, vol. 15(1), pages 1-17, December.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2021:i:1:p:2-:d:707566
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    References listed on IDEAS

    as
    1. Francis Vitek, 2005. "The Exchange Rate Forecasting Puzzle," International Finance 0509005, University Library of Munich, Germany.
    2. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
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    Cited by:

    1. Hongcheng Ding & Xuanze Zhao & Ruiting Deng & Shamsul Nahar Abdullah & Deshinta Arrova Dewi, 2024. "EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods," Papers 2408.13214, arXiv.org, revised Jun 2025.
    2. Kazım Berk Küçüklerli & Veysel Ulusoy, 2024. "Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(3), pages 1-4.
    3. Paresh Date & Janeeta Maunthrooa, 2025. "Modelling and Forecasting of Exchange Rate Pairs Using the Kalman Filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 606-622, March.
    4. Miguel Alves Pereira, 2025. "Predictive economics: Rethinking economic methodology with machine learning," Papers 2510.04726, arXiv.org.
    5. Simiso MSOMI & Harold NGALAWA, 2023. "The Movement of Exchange Rate and Expected Income: Case of South Africa," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 7(2), pages 65-89.

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