Trading on short-term path forecasts of intraday electricity prices

Tomasz Serafin, Grzegorz Marcjasz and Rafał Weron

Energy Economics, 2022, vol. 112, issue C

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 two well performing literature benchmarks by over 30%. Moreover, the forecasts provide empirical evidence that the increased computational burden induced by generating realistic price paths is offset by higher trading profits. Still, the proposed approximate and bootstrap-based methods offer a reasonable trade-off — they do not require generating path forecasts and yield only slightly lower profits.

Keywords: Intraday electricity market; Probabilistic forecast; Path forecast; Prediction bands; Trading strategy (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Trading on short-term path forecasts of intraday electricity prices (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:112:y:2022:i:c:s014098832200281x

DOI: 10.1016/j.eneco.2022.106125

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