High-dimensional high-frequency time series prediction with a mixed integer optimisation method
Please always quote using this URN: urn:nbn:de:0297-zib-93068
accepted for publication
- We study a functional autoregressive model for high-frequency time series. We approach the estimation of the proposed model using a Mixed Integer Optimisation method. The proposed model captures serial dependence in the functional time series by including high-dimensional curves. We illustrate our methodology on large-scale natural gas network data. Our model provides more accurate day-ahead hourly out-of-sample forecast of the gas in and out-flows compared to alternative prediction models.
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| Author: | Nazgul Zakiyeva, Milena Petkovic |
|---|---|
| Document Type: | Article |
| Parent Title (English): | Operations Research Proceedings |
| Date of first Publication: | 2023/12/19 |
| ISSN: | 1438-0064 |
| Preprint: | urn:nbn:de:0297-zib-93114 |
