Prediction Of the Impact of The Exchange Rate Between Euro and US Dollar Based on BP Neural Network

Abstract

In order to forecast the euro's future exchange rate against the US dollar while on the subsequent years., the writers use the self-programmed backpropagation neural network to import the opening and closing rates of the exchange rate for the latest 10 years from the US dollar to the euro and selects 1044 sets of data from them. Among them, 844 sets are used as the training set and the test set is comprised of the remaining 200 sets. A training model is established and then the nonlinear exchange rate changes are predicted using this training model. After repeated random simulation, conclusions are drawn, and results with a reasonable gap between the actual data are obtained to complete the training and finally achieve the purpose of prediction. Judging from the final experimental results, this training model has a high accuracy, and the backpropagation neural network is expected to achieve a rapid, relatively accurate and valuable prediction of the Euro to US dollar conversion rate. In the meantime, it can also provide some suggestions for the future data model from this experiment and put forward suggestions for correction.