A0364
Title: High-dimensional high-frequency time series prediction model solved with a mixed integer optimisation method
Authors: Nazgul Zakiyeva - Technische Universitat Berlin (Germany) [presenting]
Abstract: A network functional autoregressive model is studied for large-scale network time series. We approach the estimation of the proposed model using a mixed integer optimisation method. By including the high-dimensional curves, the proposed model captures both serial and cross-sectional dependence in the functional time series network. We illustrate our methodology on large-scale natural gas network data where our model provides more accurate several days-ahead hourly out-of-sample forecasts of the gas in- and out-flows compared to alternative prediction models.
