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.

翻译：预测中的不确定性量化是能源交易领域的重要议题，理解能源市场状态可帮助交易者直接评估自身报价/投标的影响。为此，我们提出一种可扩展方法，在时间序列框架内为多元函数响应变量生成闭式联合预测带。该方法能在特定条件下保证无条件覆盖率和渐近精确性的性能边界。在通过合成数据评估其性能后，该方法被用于构建意大利天然气市场日度需求与报价曲线的多元预测带。