Combining algorithms based on robust estimation techniques and co-integrating restrictions

This paper will motivate alternative combining schemes, provide a statistic for comparing alternative combinations out-of-sample and provide an example demonstrating these techniques. The evidence suggests the proposed procedures are likely to do no worse than other approaches and promise to do better under circumstances commonly encountered with economic data: integrated series and contaminated data.     

Invited review combining forecasts—twenty years later

The combination of forecasts is a simple, pragmatic and sensible way to possibly produce better forecasts. Simple extensions of the original idea involve the use of various available ‘forecasts’ even if some are rather inefficient. Some unsolved questions relate to combining forecasts with horizons longer than one period. More complicated extensions are associated with ‘encompassing’ and the combination of confidence intervals or quantiles. The relevance of information sets is emphasized in both the underlying theory and the interpretation of combinations.