consequent forecasting of a component to deal with trends and seasonality in the data. While the short-term seasonal components … electricity spot price modeling the importance of the seasonal decomposition is neglected and the problem of forecasting it is not … considered. With this paper we want to fill the gap and present a thorough study on estimation and forecasting of the LTSC of …

We present the results of an extensive study on modeling and forecasting of the long-term seasonal component (LTSC) of … decompositions and wavelet smoothers. We find that in terms of forecasting EEX and Nord Pool spot prices up to a year ahead, wavelet …

terms of forecasting these prices up to a year ahead than the commonly used monthly dummies and sine-based models. However …

and Vector ARX models) and indirectly (via factor models). The forecasting performance of five econometric models is …

for testing the ownership-structure / diversification relationship. It consists of a dynamic procedure based on wavelets …

This paper provides detailed information on Team Poland’s approach in the electricity price forecasting track of GEFCom …2014. A new hybrid model is proposed, consisting of four major blocks: point forecasting, pre-filtering, quantile …

forecasting models available for averaging. We show that the resulting Factor Quantile Regression Averaging (FQRA) approach …

regression (QR) and a pool of point forecasts of different time series models.We find that in terms of interval forecasting of …