Title: Interval prediction of electricity prices: A robust approach
Authors: Luigi Grossi - University of Verona (Italy) [presenting]
Lisa Crosato - University of Milano-Bicocca (Italy)
Fany Nan - Joint Research Center of the European Commission Ispra (Italy)
Abstract: A doubly robust approach is introduced in order to model the volatility of electricity spot prices, minimizing the misleading effects of the extreme jumps that characterize this particular kind of data on the predictions. With respect to the mainstream literature on electricity price forecasting, which highlights the importance of predicting spikes, the attention is moved to the correction of the impact that spikes have on the estimation of the prices and, in particular, on their volatility. Volatility of electricity prices has often been estimated through GARCH type models which can be strongly affected by the presence of extreme observations. Although the presence of spikes is a well-known stylized effect observed on electricity markets, robust volatility estimators have not been so far applied. We try to fill this gap by suggesting a robust procedure to the study of the dynamics of electricity prices. The conditional mean of de-trended and seasonally adjusted prices is modeled though a robust estimator of SETAR processes based on a polynomial weighting function, while a robust GARCH is used for the conditional variance. The robust GARCH estimator relies on the extension of the forward search. The robust SETAR-GARCH model is applied to the Italian electricity markets using data in the period spanning from 2013 to 2015.