臺灣博碩士論文加值系統

　　本篇論文主要在檢視Fong與See (2001) 所提出的假說，將其應用於道瓊歐洲石油天然氣指數期貨 (DJ EURO STOXX OIL & GAS Index Futures) 上，是否能得到相同的驗證。

　　在是否加入狀態轉換考量的檢定中，本文採用AIC與BIC準則為判斷的基準，而由於雙狀態下BIC準則易有樣本參數過大的懲罰特性，因此其中又以AIC為較佳判斷的準則。研究結果顯示，有考量狀態轉換的Regime Switching GARCH模型配適度會較無考量狀態轉換的GARCH模型為佳。而在納入狀態轉換的考量下，在Regime Switching GARCH模型及其相關衍生模型的比較中，主要是採用RS-GARCH(1,1)-N，RS-GARCH(1,1)-t以及RS-ARCH(1,1)-t模型作為比較。這裡同樣以AIC與BIC準則為判斷的基準，研究結果顯示，在三模型中，是以RS-GARCH(1,1)-t模型具有最佳的配適度。

　　在預測能力的檢定中，本研究是利用MSE、MAE與R2，來判斷何者具有較佳的解釋能力，並且以DM檢定來進一步驗證。研究結果顯示，在有考量狀態轉換的Regime Switching GARCH模型與無考量狀態轉換的GARCH模型中，是以有考量狀態轉換的Regime Switching GARCH模型具有較佳的預測能力；而在RS-GARCH(1,1)-N，RS-GARCH(1,1)-t以及RS-ARCH(1,1)-t三種衍生模型的比較中，又以同時考量t分配以及有狀態轉換的RS-GARCH(1,1)-t模型具有較佳的預測能力。

第壹章　緒論 4
第一節　研究背景 5
第二節　研究動機 7
第三節　研究問題與目的 9
第四節　論文架構以及研究流程 10
第貳章　文獻回顧 12
第一節　Regime Switching GARCH模型 12
第二節　Hedging 16
第參章　研究方法 17
第一節　研究標的 17
第二節　模型設定 21
第三節　模型檢定方法 25
第四節　檢定流程 28
第肆章　實證分析 29
第一節　基本資料驗證 29
第二節　模型檢定 33
第三節　模型比較 34
第四節　模型預測 37
第伍章　研究結論與建議 41
附錄 43
參考文獻 44

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