透過您的圖書館登入
IP:3.144.172.115
  • 學位論文

西德州與布蘭特原油避險策略

The Hedging Strategy of Crude Oil Spot

指導教授 : ªô«Ø¨}
共同指導教授 : ³¯¥ÉÄn(Yu-Lung Chen)

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。

並列摘要


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.

參考文獻


3.李應勳(2005),「原油價格波動與避險策略之研究」,淡江大學財務金融研究所,碩士論文。
7.高峰、洪瑞成、姜世杰與李命志(2005),「價格跳躍下的最適避險策略-日經225指數現貨與期貨 」,華岡經濟論叢,第4卷第2期,頁65-90。
2.李命志、邱哲修、黃景明、陳君達(2003),「臺灣股價指數期貨最適避險策略之研究」,企業管理學報,第58卷,頁85~104。
10.Bates, D. S., (1991) “The Crash of ’87: Was it Expected? The Evidence from the Options Markets.” Journal of Finance, Vol. 46, No. 3, pp. 1009-1044.
11.Baillie, R. T. and R. J. Myers., (1991) “Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge.” Journal of Applied Econometric, Vol. 6, pp. 109-124.

被引用紀錄


陳伯杰(2014)。最小變異數避險組合的避險效益:以布蘭特原油為例〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2014.01108
陳彥廷(2012)。跳躍風險與波動傳遞效果-原油、不動產、黃金與匯率之實證研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2012.01227
楊恭勇(2012)。避險績效的決定因素〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2012.01074
林雅慧(2011)。重新檢視以變幅為基礎的混合避險模型〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2011.00954
黃薇之(2010)。重新評估DCC-GARCH及DCC-CARR模型之避險績效〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2010.00049

延伸閱讀