Forecasting exchange rate with deep belief networks

Abstract

Forecasting exchange rates is an important financial problem which has received much attention. Nowadays, neural network has become one of the effective tools in this research field. In this paper, we propose the use of a deep belief network (DBN) to tackle the exchange rate forecasting problem. A DBN is applied to predict both British Pound/US dollar and Indian rupee/US dollar exchange rates in our experiments. We use six evaluation criteria to evaluate its performance. We also compare our method to a feedforward neural network (FFNN), which is the state-of-the-art method for forecasting exchange rate with neural networks. Experiments indicate that deep belief networks (DBNs) are applicable to the prediction of foreign exchange rate, since they achieve better performance than feedforward neural networks (FFNNs).