Electricity price forecasting has become an area of increasing relevance in recent years. Despite the growing interest … proposes a new univariate hybrid model, trained, and tested on German electricity market data, based on the Seasonal Auto … and actual prices. The ability to predict the dynamics of the price of electricity on the spot market is an important …

Electricity demand is modeled as a time-varying parameters (TVP) vector autoegression with or without imposing … RMSE and MAE, and compared trough the Diebold Mariano statistic. On the other hand, forecast intervals of Bayesian models …

This paper analyzes the dynamic behavior of day-ahead spot prices in the German electricity spot market due to positive …

forecasting performances across most of the forecasting horizons. Moreover, we found that models using the VRP as an additional … forecasting performances were not statistically different for most models, and only the Principal Component Regression (PCR) and … the Partial least squares (PLS) regression were consistently excluded from the set of best forecasting models. These …

Previous studies document statistically significant evidence of crude oil return predictability by several forecasting …

and WTI in America are compared. OVX index is able to provide the optimal forecast for the volatility of Brent's future …

the major risk exposure for many investors in energy is the volatility of the electricity price, our motivation stems from … the fact that there is no single best model for forecasting such volatility. Ample evidence suggests that most of the …, one model may outperform its peers for one country's wholesale electricity price but not necessarily for other markets …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures … outperform existing dynamic conditional correlation models for forecasting future covariances. Among the new fMSV models, the … Cholesky MSV model with long memory and asymmetry shows stable and better forecasting performance for one-day, five-day and ten …