Foreign exchange forecasting system
Kayiira, Trevor Duane
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In this project we used Auto ARIMA and LSTM to make predictions and also compare the performance of these two models in the prediction of the foreign currencies. It was discovered that the LSTM model gave better accuracy than the Auto-ARIMA model in the prediction of the foreign exchange currencies. The prediction results of the models were illustrated in a web application constructed with responsive and intuitive web user interface design, which enables easy and user-friendly interpretation of the prediction results.