• Corpus ID: 248266590

Optimal reconciliation with immutable forecasts

@inproceedings{Zhang2022OptimalRW,
  title={Optimal reconciliation with immutable forecasts},
  author={Bohan Zhang and Yanfei Kang and Anastasios Panagiotelis and Feng Li},
  year={2022}
}
The practical importance of coherent forecasts in hierarchical forecasting has inspired many studies on forecast reconciliation. Under this approach, so-called base forecasts are produced for every series in the hierarchy and are subsequently adjusted to be coherent in a second reconciliation step. Reconciliation methods have been shown to improve forecast accuracy, but will, in general, adjust the base forecast of every series. However, in an operational context, it is sometimes necessary or… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 24 REFERENCES
Understanding forecast reconciliation
Forecast combination based forecast reconciliation: insights and extensions
In a recent paper, while elucidating the links between forecast combination and cross-sectional forecast reconciliation, Hollyman et al. (2021) have proposed a forecast combination-based approach to
Game-theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts
In hierarchical time series (HTS) forecasting, the hierarchical relation between multiple time series is exploited to make better forecasts. This hierarchical relation implies one or more aggregate
Stochastic coherency in forecast reconciliation
Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions
TLDR
This work proposes a new forecasting method which relaxes these unbiasedness conditions, and seeks the revised forecasts with the best tradeoff between bias and forecast variance, and presents a regularization method which allows the method to deal with high-dimensional hierarchies, and provides its theoretical justification.
Optimal non-negative forecast reconciliation
TLDR
An empirical investigation is carried out to assess the impact of imposing non-negativity constraints on forecast reconciliation over the unconstrained method, and it is observed that slight gains in forecast accuracy have occurred at the most disaggregated level.
Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization
TLDR
A new forecast reconciliation approach is proposed that incorporates the information from a full covariance matrix of forecast errors in obtaining a set of coherent forecasts and minimizes the mean squared error of the coherent forecasts across the entire collection of time series under the assumption of unbiasedness.
Temporal hierarchies with autocorrelation for load forecasting
Least Squares-based Optimal Reconciliation Method for Hierarchical Forecasts of Wind Power Generation
Wind power generation is hierarchically organized and can be aggregated/disaggregated based on geography and electrical network structure. Forecasts are required at all levels of such a hierarchy for
...
...