An Adaptive BP Algorithm with Optimal Learning Rates and Directional Error Correction for Foreign Exchange Market Trend Prediction

Abstract

In this study, a novel adaptive BP learning algorithm with optimal learning rates and directional error correction is proposed. In this algorithm, the optimal adaptive learning rates are used to adjust the weights in an adaptive and dynamical way. Meantime, the directional errors are fed back to learning process to increase the directional accuracy. For illustration and testing purposes the proposed algorithm is applied to the foreign exchange market trend prediction.