Combining Forecasts: Operational Adjustments to Theoretically Optimal Rules

David C. Schmittlein, Jinho Kim and Donald G. Morrison
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David C. Schmittlein: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Jinho Kim: Korea Air Force Academy, Department of Management and Economics, Sangsuri Namilmyon Chungwongun, Chungbuk 363-849, Korea
Donald G. Morrison: Anderson Graduate School of Management, University of California, Los Angeles, California 90024-1481

Management Science, 1990, vol. 36, issue 9, 1044-1056

Abstract: Clemen and Winkler (1985) have described the theoretical effectiveness of Winkler's (1981) formula for optimally combining forecasts. The optimality of Winkler's formula is, however, contingent on actually knowing the forecasters' statistical properties, i.e., the variances and covariances of their forecasts. In realistic applications, of course, these properties have to be estimated, usually from a set of prior forecasts. In this case we show how the "operationally optimal" combining strategy differs from Winkler's "theoretically optimal" formula. Specifically, we provide figures indicating the operationally optimal strategy for combining two forecasts. We then propose a heuristic to choose the best set of parameter estimates in combining any number of forecasters and demonstrate its effectiveness via simulation.

Keywords: combined forecasts; Akaike's Information Criterion (search for similar items in EconPapers)
Date: 1990
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Citations: View citations in EconPapers (13)

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