  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.
