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The Effectiveness of the Elliott Waves Theory to Forecast Financial Markets: Evidence from the Currency Market

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  • Eugenio D’Angelo
  • Giulio Grimaldi

Abstract

The purpose of this paper is to investigate the capability of a technical analysis to be used as a valuable tool in forecasting financial markets. After discussing the primary theoretical and methodological differences that oppose the fundamental analysis and technical analysis and introducing the Elliott waves theory, the paper focuses on the results obtained after applying this method to the currency market. The results show that during the period from 2009-2015, the exchange rate between the U.S. dollar and euro could be forecasted with great accuracy. A potential future pattern is also proposed for the exchange rate beginning in March 2017. The research confirmed the usefulness of Elliott’s model for predicting currency markets, and the effectiveness of the fundamental analysis theories generally adopted for academic studies was evaluated.

Suggested Citation

  • Eugenio D’Angelo & Giulio Grimaldi, 2017. "The Effectiveness of the Elliott Waves Theory to Forecast Financial Markets: Evidence from the Currency Market," International Business Research, Canadian Center of Science and Education, vol. 10(6), pages 1-18, June.
  • Handle: RePEc:ibn:ibrjnl:v:10:y:2017:i:6:p:1-18
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    References listed on IDEAS

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    1. Neely, Christopher J., 2002. "The temporal pattern of trading rule returns and exchange rate intervention: intervention does not generate technical trading profits," Journal of International Economics, Elsevier, vol. 58(1), pages 211-232, October.
    2. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    3. LeBaron, Blake, 1999. "Technical trading rule profitability and foreign exchange intervention," Journal of International Economics, Elsevier, vol. 49(1), pages 125-143, October.
    4. Thomas Gehrig & Lukas Menkhoff, 2006. "Extended evidence on the use of technical analysis in foreign exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 327-338.
    5. Zhu, Yingzi & Zhou, Guofu, 2009. "Technical analysis: An asset allocation perspective on the use of moving averages," Journal of Financial Economics, Elsevier, vol. 92(3), pages 519-544, June.
    6. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    7. Batyrbekova Nurlana, 2015. "Using Elliott wave Theory predictions as inputs in equilibrium portfolio models with views," Review of Business and Economics Studies, CyberLeninka;Федеральное государственное образовательное бюджетное учреждение высшего профессионального образования «Финансовый университет при Правительстве Российской Федерации» (Финансовый университет), issue 2, pages 33-45.
    8. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    More about this item

    Keywords

    technical analysis; Elliott waves; currency market;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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