2023/03/27 by Lorenzo Zambon, Zambon, Lorenzo, Arianna Agosto +5 · 1 citation
Decision Sciences · Earth and Planetary Sciences · Engineering · #62M10 (Primary) #91B84 (Secondary) #Applications (stat.AP) #FOS: Computer and information sciences #Forecasting Techniques and Applications #G.3 #Meteorological Phenomena and Simulations #Methodology (stat.ME) #Reservoir Engineering and Simulation Methods
paper · pdf · doi:10.48550/arxiv.2303.15135
openalex publication_date 2023/03/27 · openalex created_date 2023/03/31 · openalex updated_date 2026/07/28
Reconciliation enforces coherence between hierarchical forecasts, in order to satisfy a set of linear constraints. While most works focus on the reconciliation of the point forecasts, we consider probabilistic reconciliation and we analyze the properties of the distributions reconciled via conditioning. We provide a formal analysis of the variance of the reconciled distribution, treating separately the case of Gaussian forecasts and count forecasts. We also study the reconciled upper mean in the case of 1-level hierarchies; also in this case we analyze separately the case of Gaussian forecasts and count forecasts. We then show experiments on the reconciliation of intermittent time series related to the count of extreme market events. The experiments confirm our theoretical results and show that reconciliation largely improves the performance of probabilistic forecasting.