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系統識別號 U0002-2905200713103600
中文論文名稱 西德州與布蘭特原油避險策略
英文論文名稱 The Hedging Strategy of Crude Oil Spot
校院名稱 淡江大學
系所名稱(中) 財務金融學系碩士班
系所名稱(英) Department of Banking and Finance
學年度 95
學期 2
出版年 96
研究生中文姓名 王怡文
研究生英文姓名 Yi-Wen Wang
學號 694490458
學位類別 碩士
語文別 中文
口試日期 2007-05-20
論文頁數 61頁
口試委員 指導教授-邱建良
共同指導教授-陳玉瓏
委員-王凱立
委員-李命志
委員-鄭婉秀
中文關鍵字 原油期貨  厚尾分配  樣本外避險  避險績效 
英文關鍵字 Crude oil futures  Heavy tails  out of sample hedge  Hedge performance 
學科別分類 學科別社會科學商學
中文摘要 由於昂貴的石油價格,經常和經濟惡化聯繫在一起,影響全球經濟發展。因此本文以美國西德州及英國布蘭特原油為標的,針對1990年波斯灣戰爭使石油市場大幅波動的時期,以相對應的原油期貨進行避險。
本文以持有現貨部位探討空頭避險策略作為研究主題,並假設不考慮交易成本的前提下,修正誤差為常態的假設,改以Politis(2004)提出之厚尾分配,應用GARCH模型、ARJI模型、GARCH-NoVaS模型與ARJI-HT模型,針對不同避險期間,進行樣本外避險績效的評估。實證結果如下:
一、在本研究的研究期間內,假設誤差項為厚尾分配,其避險績效皆較常態假設優良,表示厚尾分配的設定能有效捕捉到資產報酬率的特性,提高模型的配適能力,提升樣本外的避險績效。
二、ARJI模型所計算之避險績效較GARCH模型優良,顯示加入跳躍的因素後,模型更能掌握在短時間內的不確定性,並精確捕捉原油價格波動性,使得避險績效較佳。
三、各模型在預測期間之避險績效,大致上均較未避險時之報酬變異降低約70%~80%,因此投資者仍可以規避其價格波動的風險。
實證結果建議投資者在進行操作時,以西德州原油期貨進行避險者,可以ARJI模型來估計;而以布蘭特原油期貨進行避險者,以GARCH-NoVaS模型來估計,不但可以較低的避險成本避險,藉以提升避險績效,降低投資風險。
英文摘要 Because of the economic recession always comes with continuous rise in price of oil. Consequently, hedging of oil price becomes a crucial important issue. Although the GARCH model can capture the volatility of price and ARJI model can capture the jump component of price, it is not good enough to correct fat-tailed property of returns distribution.
Base on the point, this paper employs the GARCH model, ARJI model and GARCH-NoVaS model that accommodate the heavy-tailed returns innovation proposed by Politis (2004) to further examine the hedge performance for crude oil commodity markets (WTI and Brent Crude Oil) under alternative hedging periods during the Gulf War in 1990.
The empirical results show that hedging during high volatility period can reduce variance about 70%~80%. The ARJI model generates superior hedge performance to GARCH model. Moreover, the assumption of GARCH residual in heavy-tail distribution is more appropriate than normal distribution, so that models which accommodate with heavy-tail returns innovation have better hedge performance than traditional return specification.
Overall, this paper suggests using the ARJI model to enhance the hedge performance for investors in WTI crude oil markets, while using the GARCH-NoVaS model to abate investment risk for them in Brent crude oil markets.
論文目次 第一章 緒 論....................... 1
第一節 研究動機與背景....................... 1
第二節 研究目的............................. 3
第三節 研究架構............................. 4
第二章 理論基礎與文獻回顧........... 6
第一節 石油期貨............................. 6
第二節 避險理論............................. 9
第三節 國內外文獻回顧....................... 17
第三章 研究方法與理論模型........... 24
第一節 單根檢定............................. 24
第二節 ARCH效果檢定......................... 28
第三節 單變量GARCH(1,1)模型................. 30
第四節 GARCH-NoVaS模型...................... 32
第五節 ARJI模型............................. 33
第六節 ARJI-HT模型................. 36
第七節 動態跳躍強度下的最適避險模型 .........37
第四章 實證結果與分析............... 41
第一節 資料來源與處理....................... 41
第二節 現貨及期貨的分配性質................. 42
第三節 樣本內估計結果....................... 46
第四節 樣本外避險實證結果................... 52
第五章 結論......................... 57
參考文獻............................ 59

【表2.1.1】 西德州與布蘭特原油期貨契約規格..............8
【表2.3.1】 1995年前文獻整理...........................17
【表4.2.1】 西德州、布蘭特現貨與期貨之基本統計量.......42
【表4.2.2】 西德州、布蘭特原油現貨時間序列資料之單根檢定(水準項)......44
【表4.2.3】 西德州、布蘭特原油現貨時間序列資料之單根檢定(差分項)......44
【表4.2.4】 西德州、布蘭特原油現貨與期貨ARCH效果檢定..........45
【表4.3.1】 西德州GARCH(1,1)模型與GARCH-NoVaS模型之估計結果..........48
【表4.3.2】 布蘭特GARCH(1,1)模型與GARCH-NoVaS模型之估計結果..........49
【表4.3.3】 西德州ARJI(1,1)模型與厚尾ARJI模型之估計結果..........50
【表4.3.4】 布蘭特ARJI(1,1)模型與厚尾ARJI模型之估計結果..........51
【表4.4.1】 西德州、布蘭特原油平均避險比率..........53
【表4.4.2】 西德州、布蘭特原油平均避險績效指數(HEI)..........53
【圖1.1.1】研究流程圖............... 4
【圖4.2.1】布蘭特、西德州現貨與期貨原始時間序列圖..... 43
【圖4.2.2】布蘭特、西德州現貨與期貨報酬率序列圖....... 43
【圖4.4.1】估計期間(550天)與避險期間(5天)之移動視窗方法.........52
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