Forecast combination-based forecast reconciliation: Insights and extensions

نویسندگان

چکیده

In this paper, we build upon a recently proposed forecast combination-based approach to the reconciliation of simple hierarchy (Hollyman R., Petropoulos F., Tipping M.E., Understanding reconciliation, European Journal Operational Research , 2021, 294, 149–160) and extend it in some new directions. particular, provide insights into nature mathematical derivation level- l conditional coherent ( L C ) point procedure for an elementary two-level hierarchy. We show that: (i) is result linearly constrained minimization quadratic loss function, with exogenous constraint given by base top level series hierarchy, which not revised; (ii) endogenous constraints may also be considered same framework, thereby resulting reconciled forecasts where both bottom time are coherently revised. addition, that (i.e., but holds case) does guarantee non-negativity forecasts, can issue cases when natural attribute variables need (e.g., sales tourism flows). Finally, consider two forecasting experiments evaluate performance various cross-sectional procedures vis-à-vis state-of-the-art procedures) fair setting. due crucial role played (possibly different) models used compute re-interpret combined H Hollyman et al. (2021) as pooling approach, accuracy improvements obtained adopting averaging strategy.

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ژورنال

عنوان ژورنال: International Journal of Forecasting

سال: 2022

ISSN: ['1872-8200', '0169-2070']

DOI: https://doi.org/10.1016/j.ijforecast.2022.07.001