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Technical analysis in foreign exchange markets: evidence from the EMS

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  • F. FernAndez-RodrIguez
  • S. Sosvilla-Rivero
  • J. Andrada-FElix

Abstract

This article assesses the economic significance of the non-linear predictability of EMS exchange rates. To that end, and using daily data for nine EMS currencies covering the 1 January 1978-31 December 1994 period, it considers nearest- neighbour non-linear predictors, transforming their forecasts into a technical trading rule, whose profitability has been evaluated against the traditional moving average trading rules, considering both interest rates and transaction costs. The results suggest that in most cases, a trading rule based on a non-linear predictor outperforms the moving average, both in terms of returns and in terms of the ideal profit and the Sharpe ratio profitability indicators.

Suggested Citation

  • F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.
  • Handle: RePEc:taf:apfiec:v:13:y:2003:i:2:p:113-122
    DOI: 10.1080/09603100210100891
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    Cited by:

    1. Francisco Perez-Bermejo & Simon Sosvilla-Rivero & Reyes Maroto-Illera, 2007. "An eclectic approach to currency crises: drawing lessons from the EMS experience," Applied Financial Economics, Taylor & Francis Journals, vol. 18(6), pages 503-519.
    2. Andrada-Félix Julián & Fernadez-Rodriguez Fernando & Garcia-Artiles Maria-Dolores & Sosvilla-Rivero Simon, 2003. "An Empirical Evaluation of Non-Linear Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-32, October.
    3. Alexandros E. Milionis & Evangelia Papanagiotou, 2008. "A Note on the Use of Moving Average Trading Rules to Test For Weak from Efficiency in Capital Markets," Working Papers 91, Bank of Greece.
    4. Simón Sosvilla-Rivero & Emma García, "undated". "Forecasting the Dollar/Euro Exchange Rate: Can International Parities Help?," Working Papers 2003-15, FEDEA.
    5. Muhammad Arif & Muddasar Hasan & Abu Bakr & Muhammad Ziaullah & Muhammad Ali Tarer, 2018. "Profitability Of The Moving Averages Technical Trading Rules In An Emerging Stock Market-A Study Of Individual Stocks Listed On Pakistan Stock Exchange," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 14(2), pages 67-76.
    6. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    7. S. Sosvilla-Rivero & R. Maroto-Illera, 2003. "Regimen changes and duration in the European Monetary System," Applied Economics, Taylor & Francis Journals, vol. 35(18), pages 1923-1933.
    8. Gómez-Puig, Marta & Sosvilla-Rivero, Simón & Ramos-Herrera, María del Carmen, 2014. "An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 133-153.
    9. Dios Palomares, Rafaela & Martínez Paz, José Miguel & Martínezcarrasco Pleite, Federico, 2006. "Including environmental variables in the effi ciency analysis: A three-step method/El análisis de efi ciencia con variables de entorno: un método de programas con tres etapas," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 24, pages 477-497, Abril.
    10. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    11. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    12. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    13. Muhammad Arif & Muddasar Hasan & Abu Bakr & Muhammad Ziaullah & Muhammad Ali Tarer, 2018. "Profitability Of The Moving Averages Technical Trading Rules In An Emerging Stock Market-A Study Of Individual Stocks Listed On Pakistan Stock Exchange," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 14(2), pages 14-16.
    14. Elaine Y. L. Loh, 2007. "An alternative test for weak form efficiency based on technical analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(12), pages 1003-1012.
    15. Jia Wang & Tong Sun & Benyuan Liu & Yu Cao & Degang Wang, 2021. "Financial Markets Prediction with Deep Learning," Papers 2104.05413, arXiv.org.
    16. Alexandros Milionis & Evangelia Papanagiotou, 2009. "A study of the predictive performance of the moving average trading rule as applied to NYSE, the Athens Stock Exchange and the Vienna Stock Exchange: sensitivity analysis and implications for weak-for," Applied Financial Economics, Taylor & Francis Journals, vol. 19(14), pages 1171-1186.
    17. Alexandros E. Milionis & Evangelia Papanagiotou, 2013. "Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non-linear dependencies in stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(11), pages 2480-2494, November.
    18. Giuseppe Galloppo, 2009. "Dynamic Asset Allocation Using a Combined Criteria Decision System," Accounting & Taxation, The Institute for Business and Finance Research, vol. 1(1), pages 29-44.
    19. Robert Kremer & Sherrill Shaffer, 2007. "Improving the accuracy of forward exchange rate forecasts by correcting for prior bias," Applied Financial Economics, Taylor & Francis Journals, vol. 17(18), pages 1469-1478.
    20. Emma Garcia & Simón Sosvilla-rivero, 2005. "Forecasting the dollar|euro exchange rate: are international parities useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(5), pages 369-377.
    21. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    22. Jia Wang & Tong Sun & Benyuan Liu & Yu Cao & Hongwei Zhu, 2021. "CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets," Papers 2104.04041, arXiv.org.
    23. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.

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