Regression neural network for error correction in foreign exchange forecasting and trading (original) (raw)

Computers & Operations Research, 2004

Abstract

Predicting exchange rates has long been a concern in international finance as most standard econometric methods are unable to produce significantly better forecasts than the random walk model. Recent studies provide some evidence for the ability of using multivariate time series models to generate better forecasts. At the same time, artificial neural networks have been emerging as alternatives to predict

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