Trading on short-term path forecasts of intraday electricity prices

Tomasz Serafin, Grzegorz Marcjasz and Rafał Weron

No WORMS/20/17, WORking papers in Management Science (WORMS) from Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology

Abstract: We introduce a profitable trading strategy that can support decision-making in continuous intraday markets for electricity. It utilizes a novel forecasting framework, which generates prediction bands from a pool of path forecasts or approximates them using probabilistic price forecasts. The prediction bands then define a time-dependent price level that, when exceeded, indicates a good trading opportunity. Results for the German intraday market show that, in terms of the energy score, our path forecasts beat a well performing similar-day benchmark by over 25%. Moreover, they provide empirical evidence that the increased computational burden induced by generating realistic price paths is offset by higher trading profits. Still, the proposed approximate method offers a reasonable trade-off - it does not require generating path forecasts and yields only slightly lower profits.

Keywords: Intraday electricity market; Probabilistic forecast; Path forecast; Prediction bands; Energy score; Trading recommendations (search for similar items in EconPapers)
JEL-codes: C22 C32 C51 C53 Q41 Q47 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2020-12-30
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
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Downloads: (external link)
https://worms.pwr.edu.pl/RePEc/ahh/wpaper/WORMS_20_17.pdf Original version, 2020 (application/pdf)

Related works:
Journal Article: Trading on short-term path forecasts of intraday electricity prices (2022)
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