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An effective foreign exchange (Forex) trading decision is usually dependent on effective forex forecasting. This paper reports empirical evidence that an artificial neural network (ANN) is applicable to the prediction of foreign exchange rates. The architecture of the network and the related algorithms are described. The effects of the choice of inputs into a neural network model are examined. Except for the normally used time series data and technical indicators, fundamental indicators such as interest rates and gross domestic products are fed into the neural networks to see if any relationship may be captured and improve the predictive capabilities of the model.
Eng et al. (Mon,) studied this question.
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