Rank-Based Selection Strategies for Forecast Combinations: An Evaluation Study
This thesis evaluates four of the most popular methods for combining time series forecasts. One aspect that is often overlooked in the literature is the choice of which forecasts to include in a forecast combination. The focus here, is to investigate the variability in forecast accuracy that occurs between all distinct subsets from a fixed set of eleven individual forecasting models that a combina