Electricity price time series usually exhibit some form of nonstationarity, corresponding to long-term behavior, one or … more periodic components as well as dependence on calendar effects. As a result, modeling electricity prices requires … electricity price time series filtering. …

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. …

In the last few years we have observed the deregulation in electricity markets and an increasing interest in price … Italian Electricity Spot market since it has been deregulated recently. Therefore, this contribution is an investigation with … 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 …

In the context of the liberalized and deregulated electricity markets, price forecasting has become increasingly … price forecasting, the subclasses of methods based on stochastic time series and causal models commonly provide point … GAMLSS forecasting performance with published results obtained by different models. The study points out that the GAMLSS …

Recently regime-switching models have become the standard tool for modeling electricity prices. These models capture … the main properties of electricity spot prices well but estimation of the model parameters requires computer intensive … electricity market. The results are in accordance with the results from the simulation study, indicating that the proposed model …

The recent deregulation of the electricity industry and reliance on competitive wholesale markets has generated … significant volatility in wholesale electricity prices. Given the importance of short-term price forecasts in this new environment …, this paper estimates and evaluates the forecasting performance of four ARMAX–GARCH models for five MISO pricing hubs …

electricity prices. We apply seven averaging and one selection scheme and perform a backtesting analysis on day-ahead electricity … Averaging (BMA) – turn out to be unsuitable for predicting day-ahead electricity prices. …

forecasting accuracy can be improved after adding oil variables to the traditional predictors. The forecasting gains relative to …

forecasting the conditional volatility of oil spot and futures prices using a variety of GARCH-type models. Our results can be …