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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2303.15135 |
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| _version_ | 1866917589378138112 |
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| author | Zambon, Lorenzo Agosto, Arianna Giudici, Paolo Corani, Giorgio |
| author_facet | Zambon, Lorenzo Agosto, Arianna Giudici, Paolo Corani, Giorgio |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_15135 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Properties of the reconciled distributions for Gaussian and count forecasts Zambon, Lorenzo Agosto, Arianna Giudici, Paolo Corani, Giorgio Applications Methodology 62M10 (Primary), 91B84 (Secondary) G.3 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. |
| title | Properties of the reconciled distributions for Gaussian and count forecasts |
| topic | Applications Methodology 62M10 (Primary), 91B84 (Secondary) G.3 |
| url | https://arxiv.org/abs/2303.15135 |