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系統識別號 U0026-0812200914211112
論文名稱(中文) 現貨與期貨避險策略檢討-以白金為例
論文名稱(英文) Hedging Strategy for Platinum Futures and Spot Prices
校院名稱 成功大學
系所名稱(中) 企業管理學系專班
系所名稱(英) Department of Business Administration (on the job class)
學年度 96
學期 2
出版年 97
研究生(中文) 蔡冬旭
研究生(英文) Tung-Hsu Tsai
學號 r4795114
學位類別 碩士
語文別 中文
論文頁數 39頁
口試委員 口試委員-徐永明
指導教授-江明憲
口試委員-陳安琳
中文關鍵字 避險比率  避險組合  避險期間 
英文關鍵字 Hedging period  Hedging portfolio  GARCH  Bi-GARCH  Hedging ratio 
學科別分類
中文摘要 由於近幾年金屬原料價格不斷攀升,許多倚賴金屬原物料來加工製成產品的廠商就面臨了成本逐漸增加的困擾,價格的攀升除了增加廠商的成本以外,在波動的時候亦有可能讓相關廠商或者買主損失慘重,以白金為例,最近五六年當中,白金的價格從原本的每盎司500美金左右漲至目前(2008年6月)左右的2000美金每盎司,漲幅幾乎是300%而中間也不乏幾次嚴重的價前回跌,許多廠商的利潤都非常有可能在價格波動之中被吞沒,因此本研究希望以白金為例進行避險組合持有期間的研究。
本研究利用了最近年白金期貨、白金現貨價格歷史資料(2003年 1月至 2008年3月),加入同時期台幣對美元之匯率,在樣本內利用移動式窗(moving window)找出不同的避險比例,套入樣本外之避險策略求出一系列報酬率之時間函數,將時間序列之報酬函數與未搭配避險策略之投資組合做比較,檢討其避險績效,看經過不同的持有期間以及不同投資組合搭配下有怎樣的避險效果(Hedging Effectiveness)。
研究結果發現:
1. 以GARCH所得之避險比例比OLS、Bivariate -GARCH的避險效果來得好。
2. 避險期間長短影響避險績效,以白金現貨與期貨來說,避險期間一個月的表現優於避險期間二個月以及三個月。
3. 以原貨幣(美金)操作避險組合,持有期間較短避險績效普遍較好。
4. 若將避險組合加入台幣匯率轉換,則避險效果將受到影響。
英文摘要 In recent years, the prices of metal raw materials are keeping raising as the demands are obviously larger than the limited supply. The increasing metal raw material prices are becoming key cost factors to the manufacturers and consumers in the related field. The increasing price is not only increasing the cost of the related manufacturers and consumers during the prices fluctuation, the price also causes the damage to the benefit of the business in the filed. Taking Platinum as an example, the price of Platinum was around 500 USD/Troy Ounce and it has now (2008/06)risen up to 2000 USD/Tory Ounce. So that the cost raised almost 300% and during the same time it also has some depreciation. The related owner of this metal could lose a huge amount of profit from the price fluctuation. The study is to take Platinum as an example to examine the hedging effectiveness in different hedging periods.

The study used the historical data of Platinum futures, Platinum spot prices from January 2003 to March 2008. The study uses moving window to estimate the hedging ratios with different methodologies and with different hedging periods. By so, we gathered a series of returns which is the results from our hedging portfolios. We compare the variations of hedged return series with un-hedged return series so that we have the hedging effectiveness. After the study we found as below:

1.GARCH hedging ratio is performing better than OLS and Bi-variate GARCH.
2.Hedging period is affecting the performance of the hedging portfolios, the shorter of the hedging period the better the hedging effectiveness is.
3.While taking original currency (USD) as the currency used in the hedging portfolios, the shorter hedging periods is performing better than the longer hedging periods.
4.Exchanging rates could affect the hedging effect.
論文目次 摘要 --------------------------------- 0
第一章: 緒論 研究被警動機與目的
第一節: 研究動機 --------------------------------- 1
第二節: 研究目的與研究流程 ------------------------ 2
第二章: 介紹 世界白金期貨線或概況
第一節: 白金 --------------------------------- 4
第二節: 期貨 --------------------------------- 5
第三節: 白金期貨------------------------------ 7
第三章: 研究方法與歷史文獻
第一節: 文獻回顧------------------------------ 9
第二節: 國外實證文獻-------------------------- 10
第三節: 研究方法 ---------------------------- 14
第四章: 實證結果 -------------------------------- 20
第五章: 結論 -------------------------------- 26
參考文獻 -------------------------------- 27
附錄 -------------------------------- 29
參考文獻 (一)中文部分
江文強(民86),股價指數期貨避險效果之研究,交通大學管理科學研究所未出版碩士論文
林威助 (民 92),多變量GARCH架構下股價指數期貨避險策略之研究。國立台北大學企業管理學系碩士論文。
林茂南(民88),股票投資組合運用台指期貨避險策略之研究,銘傳大學金融研究所未出版碩士論文
黃景明 (民90),台灣股價指數期貨指數避險策略之研究,淡江大學金融學系碩士論文。
張哲宇(民86),股價指數期貨避險比率之研究,台灣工業技術學院管理技術研究所未出版碩士論文
羅莉莉 (民 93),期貨交易市場交叉避險策略分析-以銅商品為例,私立中原大學會計學系碩士倫文。

(二)_英文部分
Baillie, R., Myers, R., 1991. Bivariate GARCH estimation of the optimal commodity futures hedge. Journal of Applied Econometrics 6, 109-124.
Bollerslev, T., 1986. Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics 31, 307-327.
Bollerslev, T., 1988. On the correlation structure for the generalized autoregressive conditional heteroscedastic process. Journal of Time Series. Anal. 9, 121-131.
Bollerslev, T., Engle, R., Wooldridge, J., 1988. A capital asset pricing model with time-varying covariances. Journal of Political Economics. 96, 116-131.
Bollerslev, T., Chou, R., Kroner, K., 1992. ARCH modeling in finance. Journal of Econometrics 52, 5-59.
Figlewski, S., 1984. Hedging performance and basic risk in stock index futures. Journal. Finance 39, 657-669.
Fortune, P., 1989. An assessment of financial market volatility: bills, bonds, and stocks. New England Economic Review. Federal Reserve Bank of Boston, November/December, pp. 13-28.
Frino, A., Walter, T., West, R., 2000. The lead-lag relationship between equities and stock index futures markets around information releases. Journal of Futures Markets 20, 467-488.
Ghosh, A., 1993. Cointegration and error correction models: intertemporal causality between index and
futures prices. Journal of Futures Markets 13, 193_/198.
Lee, T., 1994. Spread and volatility in spot and forward exchange rates. J. Int. Money Finance 13, 375-383.
Myers, R., 1991. Estimating time varying hedge ratios on futures markets. J. Futures Markets 11, 39-53.
Park, T., Switzer, L., 1995. Time-varying distribution and the optimal hedge ratios for stock index futures. Journal of Applied Financial Economics. 5, 131-137.
Demirer and Lien. 2003. Downside risk for short and long hedgers. International Review of Economics and Finance 12 (2003) 25-44.
Choudhry. 2003. Short-run deviations and optimal hedge ratio: evidence from stock futures. Journal of Multinational Financial Management. 13 (2003) 171-192.
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