| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5097130 | Journal of Econometrics | 2007 | 31 Pages |
Abstract
This paper considers forecasts with distribution functions that may vary through time. The forecast is achieved by time varying combinations of individual forecasts. We derive theoretical worst case bounds for general algorithms based on multiplicative updates of the combination weights. The bounds are useful for studying properties of forecast combinations when data are non-stationary and there is no unique best model.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Alessio Sancetta,