Show simple item record

Sliding simulation: a new approach to time series forecasting

dc.contributor.authorMakridakis, Spyros
dc.date.accessioned2015-12-07T15:50:10Z
dc.date.available2015-12-07T15:50:10Z
dc.date.issued1990-04
dc.identifier.urihttp://hdl.handle.net/11728/6353
dc.description.abstractThis paper proposes a new approach to time series forecasting based upon three premises. First, a model is selected not by how well it fits historical data but on its ability to accurately predict out-of-sample actual data. Second, a model/method is selected among several run in parallel using out-of-sample information. Third, models/methods are optimized for each forecasting horizon separately, making it possible to have different models/methods to predict each of the m horizons. This approach outperforms the best method of the M-Competition by a large margin when tested empirically with the 111 series subsample of the M-Competition data.en_UK
dc.language.isoenen_UK
dc.publisherInstitute for Operations Research and the Management Sciencesen_UK
dc.relation.ispartofseriesJournal Management Science;Volume 36
dc.rights© 1990, The Institute of Matiagement Sciencesen_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectForecastingen_UK
dc.subjectTime seriesen_UK
dc.subjectAccuracy measuresen_UK
dc.subjectM-Competitionen_UK
dc.subjectSliding simulationen_UK
dc.titleSliding simulation: a new approach to time series forecastingen_UK
dc.typeArticleen_UK
dc.doihttp://dx.doi.org/10.1287/mnsc.36.4.505


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

© 1990, The Institute of Matiagement Sciences
Except where otherwise noted, this item's license is described as © 1990, The Institute of Matiagement Sciences