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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.
Author:Nazgul Zakiyeva, Milena Petkovic
Document Type:Article
Parent Title (English):Operations Research Proceedings
Date of first Publication:2023/12/19
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