Time Series Analysis of Grain Futures Prices: Comparison of Short Term Forecasting
Date Issued
2008
Date
2008
Author(s)
Wong, Chin-Dee
Abstract
The purpose of this thesis aims to establish short-term forecasting models for the futures prices of grains. ARMA-GARCH, level VAR, and differenced VAR model models are chosen here to analyze the dynamic interactions among wheat, soybeans and Corn traded in Chicago Board of Trade and the spot price of crude oil in the western Texas. Then, these interesting relations are applied to predict grain prices 3-month in advance. udged purely by model forecastability, the empirical results have shown that the ARMA-GARCH model performs better than other two VAR models in the grain futures prices considered. The impulse response analysis and the forecast error variance decomposition further indicate that oil price directly impacts the futures prices of corn, and oil and corn prices later push the wheat and soybeans prices. In short, these grains are closely related with the rising oil prices which makes those grain futures prices go up.
Subjects
Grain futures prices, Forecasting
VAR
GARCH
Wilcoxon
Forecast error variance decomposition
Impulse response function
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-97-R95627017-1.pdf
Size
23.53 KB
Format
Adobe PDF
Checksum
(MD5):981f373b4422f3bf04d0bf0d8dc64629