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系統識別號 U0002-0209201114443900
中文論文名稱 中國商品期貨之交叉避險績效探討
英文論文名稱 Cross Hedging with Commodity Futures in China
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 99
學期 2
出版年 100
研究生中文姓名 鄭郁儒
研究生英文姓名 Yu-Ju Cheng
學號 698530044
學位類別 碩士
語文別 英文
第二語文別 中文
口試日期 2011-05-21
論文頁數 38頁
口試委員 指導教授-邱建良
共同指導教授-白東岳
委員-李命志
委員-俞海琴
委員-蔡健雄
中文關鍵字 大連商品期貨交易  大豆油期貨  交叉避險  市場指數  雙變量 GARCH 
英文關鍵字 Dalian Commodity Exchange  soybean oil futures  market index  cross-hedging performance  Bivariate GARCH 
學科別分類 學科別社會科學商學
中文摘要 中國大陸近十年來已漸漸站穩全球供需市場之重要地位,中國之期貨交易亦
有驚人的成長,大豆油期貨交易量於自上市後短短四年內為世界第二大農產品期
貨合約。本文選用大連交易所交易最活絡的大豆油期貨作為避險工具,採用雙變
量 GARCH,GJR-GARCH 模型估計動態避險比率,進而評估樣本外避險績效,
以持有農產品現貨的投資人或機構法人為研究對象, 探討大豆油期貨在現貨市
場之交叉避險績效與策略。在現貨市場方面,本研究自中國兩大股票交易所,上
海交易所及深圳交易所挑選出 17 支農產類股,採用市值加權與價格加權法,編
制農產類股市場指數作為農產類股市場績效之代理變數。

實證結果指出:股價指數與大豆油期貨之報酬,兩者存在波動叢聚之特性(即
拒絕同質變異之假設),此亦說明採用 GARCH 模型的適切性。由於農產品現貨
具有中長期之生長週期特性,因此透過雙變量 GARCH 及 GJR-GARCH 模型捕捉
此特性,避險績效在中長期的避險期間表現較佳,隨著避險期間的延展,避險績
效有更顯著的提升。最後,農產品現貨價格受供需狀況影響較深,價格波動亦容
易受到天候因素影響,因此相較於週避險,日避險策略更能有效地使投資組合變
異數下降。
英文摘要 This study primarily examines the cross-hedging performance with the most
actively traded contract, soybean oil futures on Dalian Commodity Exchange. Unlike
previous studies, we constructed two market indices for agribusiness companies listed
on the Shanghai Stock Exchange and the Shenzhen Stock Exchange as proxy for
stock market performance. Based on the bivariate GARCH-type framework,
important evidences are illustrated in our empirical results and it provides global
traders with worthwhile implications for optimal utilization of futures contracts.
To improve the weakness of symmetric GARGH model, we employ the
GJR-GARCH model to capture the asymmetric effect in volatility of financial
variables. Owing to the implementation of the split share structure reform in 2005,
more tradable shares on stock market might lead to a substantial increase in liquidity.
Further, since the existence of the cycle in agricultural crop production, the hedge
period length and hedging frequency serve a vital role in agricultural futures hedging.
Our finding offers insightful suggestion for domestic individuals and institutional
shareholders who suffer from the price fluctuation in agricultural market.
論文目次 ABSTRACT IN CHINESE........................................................................... I
ABSTRACT IN ENGLISH .........................................................................II
ACKNOWLEDGEMENTS....................................................................... IV
LIST OF TABLES .......................................................................................V
LIST OF FIGURES ................................................................................... VI
1. Introduction ..................................................................................................1
2. Literature Review .........................................................................................6
2.1. Commodity Futures Market.....................................................................6
2.2. Hedge with Futures Contracts..................................................................8
3. Econometric Framework............................................................................14
3.1. Univariate GARCH Model ....................................................................14
3.2. Bivariate GARCH Model ......................................................................14
3.3. Bivariate GJR-GARCH(1,1) Model.......................................................16
3.4. Estimation of Optimal Hedge Ratios......................................................17
3.5. Hedging Performance Measure..............................................................18
4. Empirical Results and Analyses .................................................................20
4.1. Data Description and Preliminary Analyses ..........................................20
4.2. Bivariate GARCH and GJR-GARCH Model Estimates.........................24
4.3. Hedge Ratio and Hedging Effectiveness................................................25
4.4. Re-Examination Based on Different Market Index ................................27
5. Conclusions .................................................................................................32
Reference ..........................................................................................................33
Appendix...........................................................................................................38

LIST OF TABLES
Table 4.1 Summary Statistics on Return Series ................................................... 20
Table 4.2 Unit Root Test .................................................................................... 23
Table 4.3 Model Estimation of the Bivariate GARCH Model for Soybean Oil Futures
........................................................................................................................... 28
Table 4.4 Model Estimation of the GJR-GARCH Model for Soybean Oil Futures
........................................................................................................................... 29
Table 4.5 Out-of-Sample Hedging Effectiveness (H.E.) of Bivariate GARCH Model
........................................................................................................................... 30
Table 4.6 Out-of-Sample Hedging Effectiveness (H.E.) of GJR-GARCH Model
........................................................................................................................... 30
Table 4.7 Model Estimation For Robustness Test ............................................... 31

LIST OF FIGURES
Fig. 4.1(a) Time Series Plot of MV-index and Soybean Oil Futures .................... 21
Fig. 4.1(b) Time Series Plot of PA-index and Soybean Oil Futures ..................... 21
Fig. 4.2(a) Return Series of MV-index and Soybean Oil Futures......................... 21
Fig. 4.2(b) Return Series of PA-index and Soybean Oil Futures .......................... 21
Fig. 4.3(a) Conditional Covariance of MV-index and Futures Prices ................... 22
Fig. 4.3(b) Conditional Covariance of PA-index and Futures Prices .................... 22
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