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A REEVALUATION OF THE QUASI-BAYES APPROACH TO THE LINEAR COMBINATION OF FORECASTS

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UNSPECIFIED (1995) A REEVALUATION OF THE QUASI-BAYES APPROACH TO THE LINEAR COMBINATION OF FORECASTS. JOURNAL OF FORECASTING, 14 (6). pp. 533-542. ISSN 0277-6693

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Abstract

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
ISSN: 0277-6693
Date: November 1995
Volume: 14
Number: 6
Number of Pages: 10
Page Range: pp. 533-542
Publication Status: Published
URI: http://wrap.warwick.ac.uk/id/eprint/19291

Data sourced from Thomson Reuters' Web of Knowledge

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