Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models

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dc.creatorRamirez, Octavio A.
dc.creatorFadiga, Mohamadou L.
dc.date2017-04-01T13:55:36Z
dc.date.accessioned2026-07-09T04:10:16Z
dc.descriptionThe performance of a proposed asymmetric-error GARCH model is evaluated in comparison to the normal-error- and Student-t-GARCH models through three applications involving forecasts of U.S. soybean, sorghum, and wheat prices. The applications illustrate the relative advantages of the proposed model specification when the error term is asymmetrically distributed, and provide improved probabilistic forecasts for the prices of these commodities.
dc.identifierdoi:10.22004/ag.econ.30714
dc.identifierhttps://ageconsearch.umn.edu/record/30714/files/28010071.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/30714
dc.identifier.urihttp://hdl.handle.net/123456789/545883
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/30714
dc.titleForecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models
dc.typeText

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