Forecasting the Intra-Day Spread Densities of Electricity Prices
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Abstract (arXiv)
Intra-day price spreads are of interest to electricity traders, storage and electric vehicle operators. This paper formulates dynamic density functions, based upon skewed-t and similar representations, to model and forecast the German electricity price spreads between different hours of the day, as revealed in the day-ahead auctions. The four specifications of the density functions are dynamic and conditional upon exogenous drivers, thereby permitting the location, scale and shape parameters of the densities to respond hourly to such factors as weather and demand forecasts. The best fitting and forecasting specifications for each spread are selected based on the Pinball Loss function, following the closed-form analytical solutions of the cumulative distribution functions.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 1.
4 papers.
- 2022Distributional neural networks for electricity price forecastingcited by 24
- 2024Bayesian Hierarchical Probabilistic Forecasting of Intraday Electricity Pricescited by 4
- 2025OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecastingcited by 2
- 2022Forecasting Electricity Pricescited by 0
- 2025OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting5 Feb 2025
- 2024Bayesian Hierarchical Probabilistic Forecasting of Intraday Electricity Prices8 Mar 2024
- 2022Distributional neural networks for electricity price forecasting6 Jul 2022
- 2022Forecasting Electricity Prices25 Apr 2022