Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules

Abstract

This paper investigates the predictability of spot foreign exchange rate returns from past buy-sell signals of the simple technical trading rules by using the nearest neighbors and the feedforward network regressions. The optimal choices for nearest neighbors, hidden units in a feedforward network and the training set are determined by the cross validation method which minimizes the mean square error. Although this method is computationally expensive the results indicate that it has the advantage of avoiding overfitting in noisy environments and indicate that simple technical rules provide significant forecast improvements for the current returns over the random walk model.