Abstract
AbstractThis paper assesses the potential benefits of composite forecasting methods as applied to commodity prices. Conditions under which composite forecasts are most applicable are examined. A Monte Carlo simulation and empirical examples are used to assess the benefits of composite forecasts and provide guidelines on the selection of appropriate methods. The importance of independent pieces of information and why composites cannot be a cure for poor forecasts under many realistic situations are discussed.
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