  Due to the liberalization of markets, the change in the energy mix and the
surrounding energy laws, electricity research is a dynamically altering field
with steadily changing challenges. One challenge especially for investment
decisions is to provide reliable short to mid-term forecasts despite high
variation in the time series of electricity prices. This paper tackles this
issue in a promising and novel approach. By combining the precision of
econometric autoregressive models in the short-run with the expectations of
market participants reflected in future prices for the short- and mid-run we
show that the forecasting performance can be vastly increased while maintaining
hourly precision. We investigate the day-ahead electricity price of the EPEX
Spot for Germany and Austria and setup a model which incorporates the Phelix
future of the EEX for Germany and Austria. The model can be considered as an
AR24-X model with one distinct model for each hour of the day. We are able to
show that future data contains relevant price information for future time
periods of the day-ahead electricity price. We show that relying only on
deterministic external regressors can provide stability for forecast horizons
of multiple weeks. By implementing a fast and efficient lasso estimation
approach we demonstrate that our model can outperform several other models in
the literature.
