title: Selecting single model in combination forecasting based on cointegration test and encompassing test.
abstract: 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.
authors.affiliation: Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China ; Shanghai Business School, Shanghai 200233, China.
authors.forename: Chuanjin
authors.initials: C
authors.lastname: Jiang
authors.affiliation: Shanghai Business School, Shanghai 200233, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China.
authors.forename: Fugen
authors.initials: F
authors.lastname: Song
mesh_terms: D036262:Empirical Research; D005544:Forecasting; D008962:Models, Theoretical