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
Herein, a modified weighting for combined forecasting methods is established. These weights are used...
This paper proposes a framework for the analysis of the theoretical properties of forecast combinati...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...
Copyright © 2014 Chuanjin Jiang et al.This is an open access article distributed under the Creative ...
textabstractIn this paper it is advocated to select a model only if it significantly contributes to ...
In this paper we demonstrate that forecast encompassing tests are valuable tools in getting an insig...
This paper examines the role of forecast-encompassing principles in model-specification searches thr...
In this paper we systematically compare forecasting accuracy of hypothesis testing procedures with t...
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspe...
While the combination of several or more models is often found to improve forecasts (Brandt and Bess...
This study investigates the performance of combination forecasts in comparison to individual forecas...
It is widely accepted in forecasting that a combination model can improve forecasting accuracy. One ...
This study investigates the performance of combination forecasts in comparison to individual forecas...
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, ...
A new method of assessing the comparative quality of forecasting models is introduced. This method f...
Herein, a modified weighting for combined forecasting methods is established. These weights are used...
This paper proposes a framework for the analysis of the theoretical properties of forecast combinati...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...
Copyright © 2014 Chuanjin Jiang et al.This is an open access article distributed under the Creative ...
textabstractIn this paper it is advocated to select a model only if it significantly contributes to ...
In this paper we demonstrate that forecast encompassing tests are valuable tools in getting an insig...
This paper examines the role of forecast-encompassing principles in model-specification searches thr...
In this paper we systematically compare forecasting accuracy of hypothesis testing procedures with t...
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspe...
While the combination of several or more models is often found to improve forecasts (Brandt and Bess...
This study investigates the performance of combination forecasts in comparison to individual forecas...
It is widely accepted in forecasting that a combination model can improve forecasting accuracy. One ...
This study investigates the performance of combination forecasts in comparison to individual forecas...
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, ...
A new method of assessing the comparative quality of forecasting models is introduced. This method f...
Herein, a modified weighting for combined forecasting methods is established. These weights are used...
This paper proposes a framework for the analysis of the theoretical properties of forecast combinati...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...