Abstract

We examine the performance of artificial neural networks (ANNs) for technical trading rules for forecasting daily exchange rates. The main conclusion of our attempt is that ANNs perform well, and that they are often better than linear models. Furthermore, the precise number of hidden layer units in ANNs appears less important for forecasting performance than is the choice of explanatory variables.

Recommended Citation

Philip Hans Franses and Kasper van Griensven (1998) "Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules ", Studies in Nonlinear Dynamics & Econometrics: Vol. 2: No. 4, Article 2.
http://www.bepress.com/snde/vol2/iss4/art2

Related Files

franses_code.zip (6 kB)
Code