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A Comparative Analysis of Artificial Neural Network and Autoregressive Integrated Moving Average Model on Modeling and Forecasting Exchange Rate

Authors: Diteboho Xaba, Mogari I. Rapoo


This paper examines the forecasting performance of Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) models with the published exchange rate obtained from South African Reserve Bank (SARB). ARIMA is one of the popular linear models in time series forecasting for the past decades. ARIMA and ANN models are often compared and literature revealed mixed results in terms of forecasting performance. The study used the MSE and MAE to measure the forecasting performance of the models. The empirical results obtained reveal the superiority of ARIMA model over ANN model. The findings further resolve and clarify the contradiction reported in literature over the superiority of ARIMA and ANN models.

Keywords: Exchange Rates, ARIMA, artificial neural networks models, error metrics

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