Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models

The 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.

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Year of publication:	2003
Authors:	Ramirez, Octavio A. ; Fadiga, Mohamadou L.
Published in:	Journal of Agricultural and Resource Economics. - Western Agricultural Economics Association - WAEA. - Vol. 28.2003, 01
Publisher:	Western Agricultural Economics Association - WAEA
Subject:	GARCH \| nonnormality \| skewness \| time-series forecasting \| U.S. commodity prices \| Demand and Price Analysis

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Extent:	application/pdf
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005805390