Add to ORKGWe consider different methods for combining probability forecasts. In empirical exercises, the data generating process of the forecasts and the event being forecast is not known, and therefore the optimal form of combination will also be unknown. We consider the properties of various combination schemes for a number of plausible data generating processes, and indicate which types of combinations are likely to be useful. We also show that whether forecast encompassing is found to hold between two rival sets of forecasts or not may depend on the type of combination adopted. The relative performances of the different combination methods are illustrated, with an application to predicting recession probabilities using leading indicators.Probabil...
This article is dedicated to the memory of Clive Granger, a founding editor of this journal. Its tit...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...
This paper analyzes the real-time out-of-sample performance of three kinds of combination schemes. W...
Existing approaches to combining multiple forecasts generally offer either theoretical richness or e...
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, ...
When the objective is to forecast a variable of interest but with many explanatory variables availab...
Combining forecasts have been proven as one of the most successful methods to improve predictive per...
To improve the forecasting accuracies, researchers have long been using various combination techniqu...
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspe...
Combining forecasts To improve forecasting accuracy, combine forecasts derived from methods that dif...
This chapter summarises the recent approaches to optimal forecast combination from a frequentist per...
This paper studies forecast combination from a macroeconomic perspective. We introduce the concept o...
This article is dedicated to the memory of Clive Granger, a founding editor of this journal. Its tit...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...
We consider different methods for combining probability forecasts. In empirical exercises, the data ...
This paper analyzes the real-time out-of-sample performance of three kinds of combination schemes. W...
Existing approaches to combining multiple forecasts generally offer either theoretical richness or e...
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, ...
When the objective is to forecast a variable of interest but with many explanatory variables availab...
Combining forecasts have been proven as one of the most successful methods to improve predictive per...
To improve the forecasting accuracies, researchers have long been using various combination techniqu...
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspe...
Combining forecasts To improve forecasting accuracy, combine forecasts derived from methods that dif...
This chapter summarises the recent approaches to optimal forecast combination from a frequentist per...
This paper studies forecast combination from a macroeconomic perspective. We introduce the concept o...
This article is dedicated to the memory of Clive Granger, a founding editor of this journal. Its tit...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...
This paper proposes a dynamic ensemble algorithm to combine forecasting results from multiple method...