  Uncertainty quantification in forecasting represents a topic of great
importance in energy trading, as understanding the status of the energy market
would enable traders to directly evaluate the impact of their own offers/bids.
To this end, we propose a scalable procedure that outputs closed-form
simultaneous prediction bands for multivariate functional response variables in
a time series setting, which is able to guarantee performance bounds in terms
of unconditional coverage and asymptotic exactness, both under some conditions.
After evaluating its performance on synthetic data, the method is used to build
multivariate prediction bands for daily demand and offer curves in the Italian
gas market.
