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Stealing profits: Spread-based temporal hierarchy forecasting for day-ahead electricity markets

arXiv · AI, language, vision and robotics · article · Sep 19, 2026 · UTC

Day-ahead electricity price forecasts support trading and storage decisions, but for battery arbitrage predicting intraday price spreads is more relevant than predicting individual hourly prices. Here we show that a temporal hierarchy forecasting (THieF) framework that jointly reconciles forecasts of hourly electricity prices and all intraday price spreads consistently improves performance across two major European electricity markets and three different forecasting architectures. Using five years of out-of-sample data from Germany and Spain, we obtain accuracy improvements of up to 19.7% and

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First collected: 2026-09-23T10:01:48.231Z. This is not the publication date.