Ranking probabilistic forecasting models with different loss functions
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913587072598016 |
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| author | Serafin, Tomasz Uniejewski, Bartosz |
| author_facet | Serafin, Tomasz Uniejewski, Bartosz |
| contents | In this study, we introduced various statistical performance metrics, based on the pinball loss and the empirical coverage, for the ranking of probabilistic forecasting models. We tested the ability of the proposed metrics to determine the top performing forecasting model and investigated the use of which metric corresponds to the highest average per-trade profit in the out-of-sample period. Our findings show that for the considered trading strategy, ranking the forecasting models according to the coverage of quantile forecasts used in the trading hours exhibits a superior economic performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_17743 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Ranking probabilistic forecasting models with different loss functions Serafin, Tomasz Uniejewski, Bartosz Econometrics In this study, we introduced various statistical performance metrics, based on the pinball loss and the empirical coverage, for the ranking of probabilistic forecasting models. We tested the ability of the proposed metrics to determine the top performing forecasting model and investigated the use of which metric corresponds to the highest average per-trade profit in the out-of-sample period. Our findings show that for the considered trading strategy, ranking the forecasting models according to the coverage of quantile forecasts used in the trading hours exhibits a superior economic performance. |
| title | Ranking probabilistic forecasting models with different loss functions |
| topic | Econometrics |
| url | https://arxiv.org/abs/2411.17743 |