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Selecting Single Model in Combination Forecasting Based on Cointegration Test and Encompassing Test

Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the f...

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Detalles Bibliográficos
Autores principales: Jiang, Chuanjin, Zhang, Jing, Song, Fugen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032655/
https://www.ncbi.nlm.nih.gov/pubmed/24892061
http://dx.doi.org/10.1155/2014/621917
Descripción
Sumario:Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the forecasting object. After discussing the function of cointegration test and encompassing test in the selection of single model, supplemented by empirical analysis, the paper gives the single model selection guidance: no more than five suitable single models can be selected from many alternative single models for a certain forecasting target, which increases accuracy and stability.