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

Francisco Ortiz-Arango (fortizar62@gmail.com), Agustín I. Cabrera-Llanos and Francisco Venegas-Martínez

MPRA Paper from University Library of Munich, Germany

Abstract: 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.

Keywords: Exchange rates; artificial neural network; differential neural network; tracking and forecasting. (search for similar items in EconPapers)
JEL-codes: G17 (search for similar items in EconPapers)
Date: 2014-08-01
New Economics Papers: this item is included in nep-cmp, nep-for and nep-mon
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