This paper applies three universal approximators for forecasting. They are the Artificial Neural Networks, the …

-term predictions. Due to the characteristics of the residuals, a bootstrapping method of forecasting was also used, yielding even …

compare the forecasting performance of the various volatility models in the sample periods before and after the terrorist …

In this paper we investigate the forecasting performance of the non-linear time series SETAR model by using Canadian … GDP data from 1965 to 2000. Besides the with-in-sample fit, the forecasting performance of a standard linear ARIMA model … for the same sample has also been generated for comparative purposes. Two forecasting methods, 1-step-ahead and multi …

incorporating the wavelet transform in existing forecasting methods can improve their quality. The article aims to verify this by … characteristics. We find that wavelets do improve the forecasting quality. Depending on the data's characteristics and on the … forecasting horizon we either favour a denoising step plus an ARIMA forecast or an multiscale wavelet decomposition plus an ARIMA …