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.
Ramirez, Octavio A.; Fadiga, Mohamadou L., Forecasting Agricultural Commodity Prices with Asymmetric-Error GARCH Models, Journal of Agricultural and Resource Economics, Volume 28, Issue 1, April 2003, Pages 71-85
Share on twitter
Share on facebook