| Summary: | 碩士 === 東吳大學 === 資訊管理學系 === 106 === Integrated into the economic activities of modern society, the futures market has been integrated into the society, and the public also attaches great importance to the investment in the futures market. However, there are risks of various prices occurring in the market from time to time. Now the risks are divided into the following categories: Natural disasters, national foreign exchange policies, biofuels policies, oil and crude oil price increases, agricultural product inventories, agricultural acreage,The occurrence of these futures price risks led to price changes in the futures market, and because of the relationship of these reasons, the study was extended based on past literature. This study uses source data for futures prices of the Chicago Mercantile Exchange (CME). , US Department of Agriculture (USDA) inventories and acreage, US Federal Reserve Economy Data(FRED) for oil spot prices, and study data for research variables from January 2012 to December 2017 Then, based on the data of this period, then use the R language tool as the empirical environment of this research. Firstly, the unit root test is performed and then the variables are Autoregressive model followed by Vector Autoregression model. The established VAR model makes a Granger causality test. Based on the empirical results, the time series lags of variable agricultural commodity futures price, oil spot, agricultural planting area, and agricultural product inventories are displayed, shows whether there is a causal relationship between variables.
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