臺灣博碩士論文加值系統

現今的社會經濟活動當中，期貨市場已經融入在社會當中，而民眾也相當重視期貨市場的投資，但是在市場的投資不定期還是會出現各種價格的風險，而現在的風險分為以下幾種，天氣氣候及天災、國家外匯政策、生物燃料政策、石油及原油的價格漲幅、農產品庫存量、農產品種植面積，這些期貨價格風險的出現導致了在期貨市場上的價格變動，而因為這些原因的關係本研究根據過去文獻做延伸，本研究使用來源資料為芝加哥商品交易所(Chicago Mercantile Exchange,CME)的期貨價格，美國農業部(U.S. Department Of Agriculture ,USDA)的庫存量和種植面積，美國聯邦儲備經濟資料資料(FRED)取得石油現貨價格，而研究資料時間在2012年1月至2017年12月期間的研究變數資料，然後根據這個期間的資料再使用R語言工具做為本研究的實證環境首先做單位根檢驗然後建立其變數的自我迴歸模型(Autoregressive model)接著是向量自我迴歸模型(Vector Autoregression model)，最後根據其建立的VAR模型做格蘭傑因果關係檢驗(Granger Causality test)，在研究實證結果得出研究變數農產品期貨價格、石油現貨、農產品種植面積、農產品庫存量等變數的時間序列落後期，顯示出變數與變數之間互相是否有因果關係。

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.

誌謝 I
摘要 II
Abstact III
目錄 IV
表目錄 V
圖目錄 VI
1. 緒論 1
1.1 研究背景與動機 2
1.2 研究目的 3
2. 文獻探討 4
3. 研究方法 13
3.1 研究架構 13
3.2 格蘭傑因果分析檢測 14
3.3 資料來源 16
4. 模型分析 21
4.1 平穩性檢測 21
4.2 差分平穩性檢測 22
4.3 VAR模型 23
4.4 VAR模型-格蘭傑因果關係檢測 29
5. 研究結論 33
5.1 結論 33
5.2 研究限制與建議 34
參考文獻 35

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