In this paper we suggest an approach to comparison of models' forecasting performance in unstable environments. Our … tracking how the relative forecasting performance of competing models evolves over time. We illustrate the suggested approach …

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

We propose a new time series model aimed at forecasting crude oil prices. The proposed specification is an unobserved …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

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 …

correct direction to policies adopted. Hence, studying and forecasting of gas emissions is necessary. The purpose of this … these two methods by RMSE, MAE and MAPE metrics. The results show the more accuracy of Grey system forecasting rather than …

model forecast should become the benchmark for forecasting horse races. We compare the real-time forecasting accuracy of the … forecasting models is efficient. Our second finding is that there is no single best forecasting method. For example, typically … simple AR models are most accurate at short horizons and DSGE models are most accurate at long horizons when forecasting …