Artificial Neural Networks endowed with External Factors for Forecasting Foreign Exchange Rate

The successful key of trading in the forex market is the selection of correct exchange in proper time based on an exact prediction of future exchange rate. Foreign exchange rates are affected by many correlated economic, political and even psychological factors. Therefore, in order to achieve a profitable trade these factors should be considered. The application of intelligent techniques for forecasting has been proved extremely successful in recent years. Previous studies have mainly focused on the historical prices and the trading volume of one market only. In this paper, we have used Artificial Neural Networks (ANN) to predict the exchange rate with respect to three external factors including gold, petroleum prices and FTSE 100 index. The result of forecasts is compared with the ANNs without external factors. The empirical results demonstrate that the proposed model can be an effective way of forecasting. For the experimental analysis phase, the data of exchange rate of GBP/USD is used.

Artificial Neural Networks endowed with External Factors for Forecasting Foreign Exchange Rate Keywords:

Forex market , GBP/USD , Artificial Neural Networks , Gold price , Petroleum price , FTSE