We show that incorporating the intra-day relationships of electricity prices improves the accuracy of forecasts of … daily electricity spot prices. We use half-hourly data from the UK power market to model the spot prices directly (via ARX … and Vector ARX models) and indirectly (via factor models). The forecasting performance of five econometric models is …

We show that incorporating the intra-day and inter-zone relationships of electricity prices in the Pennsylvania … a major PJM market hub -- the Dominion Hub in Virginia, U.S. The forecasting performance of four multivariate models …

This paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We …

We present the results of an extensive study on modeling and forecasting of the long-term seasonal component (LTSC) of … electricity spot prices. We consider a vast array of models including linear regressions, monthly dummies, sinusoidal … decompositions and wavelet smoothers. We find that in terms of forecasting EEX and Nord Pool spot prices up to a year ahead, wavelet …

electricity spot price modeling the importance of the seasonal decomposition is neglected and the problem of forecasting it is not …When building stochastic models for electricity spot prices the problem of uttermost importance is the estimation and … consequent forecasting of a component to deal with trends and seasonality in the data. While the short-term seasonal components …

predictive value with respect to forecasting the occurrence of electricity price spikes. We focus on information that measures …

__Abstract__ The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects … for forecasting weekly and monthly horizons. …