Comparison of auto-regressive moving average and multilayer perceptron based methods for economic time series forecasting

In this paper two popular time series prediction methods – the Auto-Regressive Moving Average and the multilayer perceptron (MLP) – are compared while forecasting seven real world economical time series. It is shown that the prediction accuracy of both methods is poor in ill-structured problems. In the well-structured cases, when prediction accuracy is high, the MLP predicts better providing lower mean prediction error.