Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures

Rick Steinert and Florian Ziel

The Energy Journal, 2019, vol. Volume 40, issue Number 1

Abstract: 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.

JEL-codes: F0 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.iaee.org/en/publications/ejarticle.aspx?id=3279 (text/html)
Access to full text is restricted to IAEE members and subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aen:journl:ej40-1-steinert

Ordering information: This journal article can be ordered from
http://www.iaee.org/en/publications/ejsearch.aspx

Access Statistics for this article

More articles in The Energy Journal from International Association for Energy Economics Contact information at EDIRC.
Bibliographic data for series maintained by David Williams ().