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Optimal Length of Moving Average to Forecast Futures Basis AgEcon
Hatchett, Robert B.; Brorsen, B. Wade; Anderson, Kim B..
The question addressed in this study is which length of historical moving average provides the best forecast of futures basis. Differences in observed forecast accuracy among the different moving averages are usually less than a cent per bushel, and most are not statistically significant. Further, the search for an optimal length of moving average may be futile since the optimal length depends on how much structural change has occurred. Our recommendation is to use moving averages when there has been no structural change and to use last year’s basis or an alternative approach if the forecaster perceives that a structural change has occurred.
Tipo: Journal Article Palavras-chave: Basis forecast; Grain; Law of One Price; Moving averages; Structural change; Marketing.
Ano: 2010 URL: http://purl.umn.edu/61057
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Optimal Length of Moving Average to Forecast Futures Basis AgEcon
Hatchett, Robert B.; Brorsen, B. Wade; Anderson, Kim B..
Futures prices when combined with a basis forecast provide a reliable way to forecast cash prices. The most popular method of forecasting basis is historical moving averages. Given the recent failure of longer moving averages proposed by previous studies, this research reassesses past recommendations about the best length of moving average to use in forecasting basis. This research compares practical preharvest and storage period basis forecasts for hard wheat, soft wheat, corn and soybeans to identify the optimal amount of historical information to include in moving average forecasts. Only with preharvest hard wheat forecasts are the best moving averages longer than 3 years. The differences in forecast accuracy among the different moving averages are...
Tipo: Conference Paper or Presentation Palavras-chave: Basis forecast; Grain; Law of One Price; Moving averages; Structural change; Agribusiness; Agricultural and Food Policy; Agricultural Finance; Crop Production/Industries; Farm Management; Financial Economics; Marketing; Research Methods/ Statistical Methods; Risk and Uncertainty.
Ano: 2009 URL: http://purl.umn.edu/53048
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