A REEVALUATION OF THE QUASI-BAYES APPROACH TO THE LINEAR COMBINATION OF FORECASTS
UNSPECIFIED (1995) A REEVALUATION OF THE QUASI-BAYES APPROACH TO THE LINEAR COMBINATION OF FORECASTS. JOURNAL OF FORECASTING, 14 (6). pp. 533-542. ISSN 0277-6693Full text not available from this repository.
The subjective forecasts used in decision analysis should, in principle, synthesize all available evidence about the subject in analysis. In this manner, when part of the evidence consists of a variety of forecasting models or expert opinions, Decision Theory requires the decision maker to formulate a combination of these predictors. This work takes into account the Bayesian methodologies outperformance and quasi-Bayes, as well as the classical model of optimal combination, all applied to the linear combination of petroleum price forecasts, generated by experts from Petrobras-the Brazilian oil company-for several international markets. It presents a theoretical description of the methodologies followed by a comparative analysis between performances of the best experts' forecasts and combinations. The performances and features of these combinations are also compared.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HD Industries. Land use. Labor
|Journal or Publication Title:||JOURNAL OF FORECASTING|
|Publisher:||JOHN WILEY & SONS LTD|
|Number of Pages:||10|
|Page Range:||pp. 533-542|
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