The paper presents an analysis of using AIRS and ESN for the prediction of future movements of the EUR/USD exchange rate. Both models, AIRS and ESN, are developed and optimized on historical price data and a number of technical indicators. In order to improve further the prediction of the upward/downturn movement, a stacking ensemble was used to combine the two models using a logistic regression meta-model. On accuracy, AIRS model test set yielded an average of 65.3% with a F1 score of 0.6108, while the ESN model, on the other hand, achieved 56.3% in accuracy and a F1 score of 0.4014. Stacking performed better in comparison to the test set of the other two subject models, with an accuracy of 69.0% and a F1 score of 0.6764. These results prove that this may give an increased way of engaging in the study of exchange rate movements through an ensemble strategy that will combine the different models. In this regard, it guarantees a significant investment tool for traders and analysts in the Forex market.