Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Market
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2021
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| _version_ | 1866911757020168192 |
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| author | Diquigiovanni, Jacopo Fontana, Matteo Vantini, Simone |
| author_facet | Diquigiovanni, Jacopo Fontana, Matteo Vantini, Simone |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2107_00527 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Market Diquigiovanni, Jacopo Fontana, Matteo Vantini, Simone Methodology Applications 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. |
| title | Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Market |
| topic | Methodology Applications |
| url | https://arxiv.org/abs/2107.00527 |