investment strategies in new power plants and grid interconnections. Implementing Reg-ARFIMA–GARCH models, we assess the … forecasting performance of selected models showing that they perform better when these factors are considered. …

large number of forecasting models have been designed to forecast crude oil prices' volatility, so far the relative … performance evaluation of competing forecasting models remains an exercise that is unidimensional in nature. To be more specific …

This article analyzes the demand for electricity and provides out-of-sample forecasting at the sectoral level using a … one would expect if the forecasting relationship is stationary. The long-run parameter estimates are then used to conduct … ex-ante forecasting under plausible assumptions for policy making. …

We present the results of an extensive study on estimation and forecasting of the long-term seasonal component (LTSC … are significantly better in terms of forecasting spot prices up to a year ahead than the commonly used monthly dummies and …

forecasting performance of econometric models incorporating asymmetric price transmission from crude oil to gasoline. In this … sign and probability forecasts. Finally, we highlight that the forecasting performance of the estimated models is time-varying. …

This article examines the volatility forecasting abilities of three approaches: GARCH-type model that uses carbon … document that GARCH-type models perform better than an implied volatility and the k-nearest neighbor model. This result …

problems. In this paper, we focus on modeling and forecasting the long-term price level, since it is the dominant factor in …

calibration. The model can be used for simulation and forecasting of electricity spot prices over short- and medium-term horizons …