Using implementation of artificial intelligence in estimating the exchange rate in the foreign exchange market

Abstract

The Foreign Exchange currency market is considered the most liquid market in the world due to the amount of money that is traded every day. Researchers and investors are interested in having a system that allows predicting the direction of the exchange rate of a pair of currencies in order to create a strategy that allows them to profit from the market. Since the movement of the exchange rate between currencies generates a high frequency time series, recurrent neural networks have gained strength in the prediction of these markets, since they have the characteristic of generating models of non-linear systems. In this document, the study of the prediction of the direction of the exchange rate of different currencies was carried out using the recurrent auto-regressive neural network with exogenous inputs, which has the characteristics to obtain a predictive model of a time series. The tests were carried out in the Euro / Dollar pair in the time frame of one hour, demonstrating the potential of this neural network architecture. These techniques are products of the biological and physical sciences in industrial processes.