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Directional forecasting in financial time series using support vector machines: The USD/Euro exchange rate

Author

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  • Plakandaras, Vasilios

    (Democritus University of Thrace, Department of International Economic Relations and Development)

  • Papadimitriou, Theophilos

    (Democritus University of Thrace, Department of International Economic Relations and Development)

  • Gogas, Periklis

    (Democritus University of Thrace, Department of International Economic Relations and Development)

Abstract

In this paper, we present a novel machine learning based forecasting system of the EU/USD exchange rate directional changes. Specifically, we feed an overcomplete variable set to a Support Vector Machines (SVM) model and refine it through a Sensitivity Analysis process. The dataset spans from 1/1/1999 to 30/11/2011; the data of the last 7 months are reserved for out-of-sample testing. Results show that the proposed scheme outperforms various other machine learning methods treating similar scenarios.

Suggested Citation

  • Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis, 2012. "Directional forecasting in financial time series using support vector machines: The USD/Euro exchange rate," DUTH Research Papers in Economics 5-2012, Democritus University of Thrace, Department of Economics.
  • Handle: RePEc:ris:duthrp:2012_005
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    References listed on IDEAS

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    1. Paul De Grauwe & Marianna Grimaldi, 2014. "Exchange Rate Puzzles: A Tale of Switching Attractors," World Scientific Book Chapters, in: Exchange Rates and Global Financial Policies, chapter 3, pages 71-117, World Scientific Publishing Co. Pte. Ltd..
    2. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
    3. MacDonald, Ronald & Nagayasu, Jun, 1998. "On the Japanese Yen-U.S. Dollar Exchange Rate: A Structural Econometric Model Based on Real Interest Differentials," Journal of the Japanese and International Economies, Elsevier, vol. 12(1), pages 75-102, March.
    4. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    5. Sarno,Lucio & Taylor,Mark P., 2003. "The Economics of Exchange Rates," Cambridge Books, Cambridge University Press, number 9780521485845, October.
    6. Altaf Hossain & Mohammed Nasser, 2011. "Comparison of the finite mixture of ARMA-GARCH, back propagation neural networks and support-vector machines in forecasting financial returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 533-551, November.
    7. Frankel, Jeffrey A, 1979. "On the Mark: A Theory of Floating Exchange Rates Based on Real Interest Differentials," American Economic Review, American Economic Association, vol. 69(4), pages 610-622, September.
    8. Serletis, Apostolos & Gogas, Periklis, 1997. "Chaos in East European black market exchange rates," Research in Economics, Elsevier, vol. 51(4), pages 359-385, December.
    9. Wei Huang & K. K. Lai & Y. Nakamori & Shouyang Wang, 2004. "Forecasting Foreign Exchange Rates With Artificial Neural Networks: A Review," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 145-165.
    10. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Bela Balassa, 1964. "The Purchasing-Power Parity Doctrine: A Reappraisal," Journal of Political Economy, University of Chicago Press, vol. 72, pages 584-584.
    13. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.
    14. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
    15. Lance Taylor, 2004. "Exchange rate indeterminacy in portfolio balance, Mundell--Fleming and uncovered interest rate parity models," Cambridge Journal of Economics, Oxford University Press, vol. 28(2), pages 205-227, March.
    16. Fama, Eugene F., 1984. "Forward and spot exchange rates," Journal of Monetary Economics, Elsevier, vol. 14(3), pages 319-338, November.
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    Cited by:

    1. Kea BARET & Theophilos PAPADIMITRIOU, 2019. "On the Stability and Growth Pact compliance: what is predictable with machine learning?," Working Papers of BETA 2019-48, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    3. Pragidis, Ioannis & Gogas, Periklis & Plakandaras, Vasilios & Papadimitriou, Theophilos, 2015. "Fiscal shocks and asymmetric effects: A comparative analysis," The Journal of Economic Asymmetries, Elsevier, vol. 12(1), pages 22-33.
    4. Rangan Gupta & Vasilios Plakandaras, 2019. "Efficiency in BRICS Currency Markets Using Long-Spans of Data: Evidence from Model-Free Tests of Directional Predictability," Journal of Economics and Behavioral Studies, AMH International, vol. 11(1), pages 152-165.

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    More about this item

    Keywords

    Machine Learning; Support Vector Machines; Exchange Rates; Forecasting;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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