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
- 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.
| Author: | Nazgul Zakiyeva, Milena Petkovic |
|---|---|
| Document Type: | Article |
| Parent Title (English): | Operations Research Proceedings 2023. OR 2023 |
| First Page: | 423 |
| Last Page: | 429 |
| Year of first publication: | 2025 |
| ISSN: | 1438-0064 |
| Preprint: | urn:nbn:de:0297-zib-93114 |
| DOI: | https://doi.org/10.1007/978-3-031-58405-3_54 |

