Forecast reconciliation: a brief overview


11 September 2023


Zalando, Berlin, Germany



Collections of time series that are formed via aggregation are prevalent in many fields. These are commonly referred to as hierarchical time series and may be constructed cross-sectionally across different variables, temporally by aggregating a single series at different frequencies, or may even be generalised beyond aggregation as time series that respect linear constraints. When forecasting such time series, a desirable condition is for forecasts to be coherent, that is to respect the constraints. The past decades have seen substantial growth in this field with the development of reconciliation methods that not only ensure coherent forecasts but can also improve forecast accuracy. This talk provides an overview of recent work on forecast reconciliation.

Associated paper

Athansopoulos, Hyndman, Kourentzes & Panagiotelis (2024) “Forecast reconcilation: a review”, International Journal of Forecasting, to appear.


Slides for IMS-APRM 2024

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Slides for TSF 2023

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Slides for Zalando and Uni of Melbourne

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