Too similar to combine? On negative weights in forecast combination

نویسندگان

چکیده

This paper provides the first thorough investigation of negative weights that can emerge when combining forecasts. The usual practice in literature is to consider only convex combinations and ignore or trim weights, i.e., set them zero. default strategy has its merits, but it not optimal. We study problem from various angles, main conclusion highly correlated forecasts with similar variances are combined. In this situation, estimated have large variances, trimming reduces variance improves combined forecast. threshold zero arbitrary be improved. propose an optimal threshold, additional tuning parameter improve forecasting performance. effects demonstrated simulations. empirical example using European Central Bank Survey Professional Forecasters, we find new performs exceptionally well deliver improvements more than 10% for inflation, up 20% GDP growth, unemployment relative equal-weight benchmark.

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ژورنال

عنوان ژورنال: International Journal of Forecasting

سال: 2023

ISSN: ['1872-8200', '0169-2070']

DOI: https://doi.org/10.1016/j.ijforecast.2021.08.002