An Approximate Bayesian Algorithm for Combining Forecasts* |
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Authors: | Kim‐Hung Li Heung Wong Marvin Troutt |
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Abstract: | In this paper we propose a consensus forecasting method based on a convex combination of individual forecast densities. The exact Bayesian updating of the convex combination weights is very complex and practically prohibitive. We propose a simple sequential updating alternative method based on function approximation. Several examples illustrate the method. |
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Keywords: | Financial Models Statistics Term Structure Time Series Forecasting |
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