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Euro Exchange Rate Forecasting with Differential Neural Networks with an Extended Tracking Procedure


  • Ortiz-Arango, Francisco
  • Cabrera-Llanos, Agustín I.
  • Venegas-Martínez, Francisco


This paper is aimed at developing a new kind of non-parametrical artificial neural network useful to forecast exchange rates. To do this, we departure from the so-called Differential or Dynamic neural Networks (DNN) and extend the tracking procedure. Under this approach, we examine the daily closing values of the exchange rates of the Euro against the US dollar, the Japanese yen and the British pound. With our proposal, Extended DNN or EDNN, we perform the tracking procedure from February 15, 1999, to August 31, 2013, and, subsequently, the forecasting procedure from September 2 to September 13, 2013. The accuracy of the obtained results is remarkable, since the percentage of the error in the predicted values is within the range from 0.001% to 0.69% in the forecasting period.

Suggested Citation

  • Ortiz-Arango, Francisco & Cabrera-Llanos, Agustín I. & Venegas-Martínez, Francisco, 2014. "Euro Exchange Rate Forecasting with Differential Neural Networks with an Extended Tracking Procedure," MPRA Paper 57720, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:57720

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    References listed on IDEAS

    1. Christian Dunis & Jason Laws & Georgios Sermpinis, 2010. "Modelling and trading the EUR/USD exchange rate at the ECB fixing," The European Journal of Finance, Taylor & Francis Journals, vol. 16(6), pages 541-560.
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    More about this item


    Exchange rates; artificial neural network; differential neural network; tracking and forecasting.;

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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