2021/07/01 by Jacopo Diquigiovanni, Matteo Fontana, Diquigiovanni, Jacopo +3 · 2 citations
Decision Sciences · Economics, Econometrics and Finance · Engineering · Mathematics · #Advanced Statistical Methods and Models #Applications (stat.AP) #FOS: Computer and information sciences #Fault Detection and Control Systems #Financial Risk and Volatility Modeling #Forecasting Techniques and Applications #Market Dynamics and Volatility #Methodology (stat.ME)
paper · pdf · doi:10.48550/arxiv.2107.00527
openalex publication_date 2021/07/01 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Uncertainty quantification in forecasting represents a topic of great\nimportance in energy trading, as understanding the status of the energy market\nwould enable traders to directly evaluate the impact of their own offers/bids.\nTo this end, we propose a scalable procedure that outputs closed-form\nsimultaneous prediction bands for multivariate functional response variables in\na time series setting, which is able to guarantee performance bounds in terms\nof unconditional coverage and asymptotic exactness, both under some conditions.\nAfter evaluating its performance on synthetic data, the method is used to build\nmultivariate prediction bands for daily demand and offer curves in the Italian\ngas market.\n