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Foreign exchange market prediction with multiple classifiers

  • Bo Qian

    (Boyd Graduate Studies Research Center, Department of Computer Science, University of Georgia, Athens, Georgia, USA)

  • Khaled Rasheed

    (Boyd Graduate Studies Research Center, Department of Computer Science, University of Georgia, Athens, Georgia, USA)

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    Foreign exchange market prediction is attractive and challenging. According to the efficient market and random walk hypotheses, market prices should follow a random walk pattern and thus should not be predictable with more than about 50% accuracy. In this article, we investigate the predictability of foreign exchange spot rates of the US dollar against the British pound to show that not all periods are equally random. We used the Hurst exponent to select a period with great predictability. Parameters for generating training patterns were determined heuristically by auto-mutual information and false nearest-neighbor methods. Some inductive machine-learning classifiers-artificial neural network, decision tree, k -nearest neighbor, and naïve Bayesian classifier-were then trained with these generated patterns. Through appropriate collaboration of these models, we achieved a prediction accuracy of up to 67%. Copyright © 2009 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.1124
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    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 29 (2010)
    Issue (Month): 3 ()
    Pages: 271-284

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    Handle: RePEc:jof:jforec:v:29:y:2010:i:3:p:271-284
    DOI: 10.1002/for.1124
    Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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    1. Manolis Kavussanos & Everton Dockery, 2001. "A multivariate test for stock market efficiency: the case of ASE," Applied Financial Economics, Taylor & Francis Journals, vol. 11(5), pages 573-579.
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    4. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    5. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    6. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    7. Butler, Kirt C. & Malaikah, S. J., 1992. "Efficiency and inefficiency in thinly traded stock markets: Kuwait and Saudi Arabia," Journal of Banking & Finance, Elsevier, vol. 16(1), pages 197-210, February.
    8. Liam A. Gallagher & Mark P. Taylor, 2002. "Permanent and Temporary Components of Stock Prices: Evidence from Assessing Macroeconomic Shocks," Southern Economic Journal, Southern Economic Association, vol. 69(2), pages 345-362, October.
    9. Marco Corazza & A. G. Malliaris, 2002. "Multi-Fractality in Foreign Currency Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 6(2), pages 65-98, June.
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