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Non-linear, non-parametric, non-fundamental exchange rate forecasting

Author

Listed:
  • Jing Yang

    (Financial Markets Department, Bank of Canada, Ottawa, Ontario, Canada)

  • Nikola Gradojevic

    (Faculty of Business Administration, Lakehead University, Thunder Bay, Ontario, Canada)

Abstract

This paper employs a non-parametric method to forecast high-frequency Canadian|US dollar exchange rate. The introduction of a microstructure variable, order flow, substantially improves the predictive power of both linear and non-linear models. The non-linear models outperform random walk and linear models based on a number of recursive out-of-sample forecasts. Two main criteria that are applied to evaluate model performance are root mean squared error (RMSE) and the ability to predict the direction of exchange rate moves. The artificial neural network (ANN) model is consistently better in RMSE to random walk and linear models for the various out-of-sample set sizes. Moreover, ANN performs better than other models in terms of percentage of correctly predicted exchange rate changes. The empirical results suggest that optimal ANN architecture is superior to random walk and any linear competing model for high-frequency exchange rate forecasting. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Jing Yang & Nikola Gradojevic, 2006. "Non-linear, non-parametric, non-fundamental exchange rate forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 227-245.
  • Handle: RePEc:jof:jforec:v:25:y:2006:i:4:p:227-245
    DOI: 10.1002/for.986
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    References listed on IDEAS

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    Cited by:

    1. Olcay Erdogan & Ali Goksu, 2014. "Forecasting Euro and Turkish Lira Exchange Rates with Artificial Neural Networks (ANN)," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 4(4), pages 307-316, October.
    2. Emekter, Riza & Jirasakuldech, Benjamas & Snaith, Sean M., 2009. "Nonlinear dynamics in foreign exchange excess returns: Tests of asymmetry," Journal of Multinational Financial Management, Elsevier, vol. 19(3), pages 179-192, July.
    3. David E. Allen & Michael McAleer & Shelton Peiris & Abhay K. Singh, 2016. "Nonlinear Time Series and Neural-Network Models of Exchange Rates between the US Dollar and Major Currencies," Risks, MDPI, Open Access Journal, vol. 4(1), pages 1-14, March.
    4. Gradojevic, Nikola, 2007. "Non-linear, hybrid exchange rate modeling and trading profitability in the foreign exchange market," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 557-574, February.
    5. Cerrato, Mario & Kim, Hyunsok & MacDonald, Ronald, 2015. "Microstructure order flow: statistical and economic evaluation of nonlinear forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 40-52.
    6. Oliver Blaskowitz & Helmut Herwartz, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers SFB649DP2008-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Tasadduq Imam & Kevin Tickle & Abdullahi Ahmed & William Guo, 2012. "Linear Relationship Between The Aud/Usd Exchange Rate And The Respective Stock Market Indices: A Computational Finance Perspective," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 19-42, January.
    8. repec:gam:jrisks:v:4:y:2016:i:1:p:7:d:65863 is not listed on IDEAS
    9. Chen, Pei-wen & Huang, Han-ching & Su, Yong-chern, 2014. "The central bank in market efficiency: The case of Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 239-260.
    10. Gradojevic, Nikola, 2007. "The microstructure of the Canada/U.S. dollar exchange rate: A robustness test," Economics Letters, Elsevier, vol. 94(3), pages 426-432, March.
    11. Angela He & Alan Wan, 2009. "Predicting daily highs and lows of exchange rates: a cointegration analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1191-1204.
    12. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, Elsevier.
    13. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.

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