Beating the naive: Combining LASSO with naive intraday electricity price forecasts

Grzegorz Marcjasz, Bartosz Uniejewski and Rafał Weron

No WORMS/20/01, WORking papers in Management Science (WORMS) from Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology

Abstract: A recent electricity price forecasting study claims that the German intraday, continuous-time market for hourly products is weak-form efficient, i.e., that the best predictor for the so-called ID3-Price index is the most recent transaction price. Here, we undermine this claim and show that we can beat the naive forecast by combining it with a prediction of a parameter-rich model estimated using the least absolute shrinkage and selection operator (LASSO). We further argue, that that if augmented with timely predictions of fundamental variables for the coming hours, the LASSO-estimated model itself can significantly outperform the naive forecast.

Keywords: Intraday electricity market; ID3-Price index; Price forecasting; Variable selection; Fundamental variables; LASSO; Averaging forecasts (search for similar items in EconPapers)
JEL-codes: C22 C32 C51 C53 Q41 Q47 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2020-02-02
New Economics Papers: this item is included in nep-ene, nep-for and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://worms.pwr.edu.pl/RePEc/ahh/wpaper/WORMS_20_01.pdf Original version, 2020 (application/pdf)

Related works:
Journal Article: Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts (2020)
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:ahh:wpaper:worms2001

Access Statistics for this paper

More papers in WORking papers in Management Science (WORMS) from Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology Contact information at EDIRC.
Bibliographic data for series maintained by Anna Kowalska-Pyzalska ().