Forecasting the Intra-Day Spread Densities of Electricity Prices

Ekaterina Abramova and Derek Bunn
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Ekaterina Abramova: London Business School, Department of Management Science and Operations, Regent’s Park, London NW1 4SA, UK
Derek Bunn: London Business School, Department of Management Science and Operations, Regent’s Park, London NW1 4SA, UK

Energies, 2020, vol. 13, issue 3, 1-31

Abstract: 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.

Keywords: electricity; spreads; forecasting; GAMLSS (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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