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研究生:吳世強
研究生(外文):Goh, Shichang
論文名稱:中國金融期貨市場避險比例之檢定 -以BEKK為研究模型
論文名稱(外文):Testing For The Chinese Finance Futures Market – A BEKK Approach
指導教授:蕭榮烈蕭榮烈引用關係
指導教授(外文):Hsiao, Junglieh
口試委員:邱建良邱靖博郭淑惠吳佩珊
口試委員(外文):Chiu, ChianliangChiu, ChingpoKuo, ShuhuiWu, Peishan
口試日期:2012-06-12
學位類別:碩士
校院名稱:國立臺北大學
系所名稱:國際企業研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:41
中文關鍵詞:避險比率BEKK到期日
外文關鍵詞:Hedge ratioBEKKTime-maturity
相關次數:
  • 被引用被引用:1
  • 點閱點閱:84
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  • 下載下載:18
  • 收藏至我的研究室書目清單書目收藏:1
隨著全球目光聚焦於歐債與美債危機當中,中國正慢慢崛起成為世界經濟強國;但相較其他經濟強國,中國金融市場開放較晚,資訊迅速傳遞與國際國際市場整合能加速經濟成長,但也為今日的金融市場增加更多的不確定性,因此,本文想藉由general modified BEKK模型探討中國滬深指數市場。

本文將滬深指數現期貨日內資料作為研究對象,並納入定性變數(到期日、政府調整、日內效果與換月效果) 。我們利用general modified BEKK模型與其它模型進行比較,提供投資人瞭解新興市場情況,妥善配置並降低風險。實證結果發現,general modified BEKK模型優於其他模型,可幫助流動性交易者(即不具訊息優勢之交易者)降低其持有投資組合的風險。

When the world is concentrating on European debt and American debt, Chinese is slowly rising to become the world's largest Economic Industry; but compare to other leading economic power, Chinese's financial market was opened late. Though rapid information communication and international market integration can speed up Chinese's economic growth, yet, it also signifies the uncertainty in its financial market today. Hence, this study will use general modified BEKK to investigate Chinese's CSI300 market.
These models uses intra data from the CSI300 spot and futures index, and accounting separately for time-maturity, government adjustment, intraday effect and turn of the month effect. We use the general Modified BEKK Model and its internal MODEL to calculate the optimal hedge ratio in order to compare which model is most effective to explain the optimal hedge ratio. Our statistical tests support a conclusion that it can effectively estimate optimal hedge ratio of Chinese's cash and futures prices in time-varying, so can it provide liquidity trader during hedging.

Contents
INTRODUCTION 1
1.1 BACKGROUND 1
1.2 MOTIVATION 2
1.3 PURPOSE 3
1.4 FRAMEWORK 3
LITERATURE REVIEW 5
2.1 INTRODUCTION OF CSI300 INDEX FUTURES CONTRACT 5
2.2 HEDGE RATIO LITERATURE 6
METHODOLOGY 9
3.1 AUGMENTED DICKEY-FULLER TEST 9
3.2 PHILLIPS-PERRON TEST 10
3.3 KPSS TEST 11
3.4 COINTEGRATION TEST 11
3.5 ARCH EFFECT TEST 13
3.6 EMPIRICAL MODEL 14
EMPIRICAL RESEARCH AND ANALYSIS 18
4.1 DESCRIBING INFORMATION 18
4.1.1 DESCRIPTIVE STATISTICS 22
4.2 EMPIRICAL RESULT ANALYSIS 25
4.2.1 UNIT-ROOT TEST 25
4.2.2 COINTEGRATION TEST 27
4.2.3 SERIAL CORRELATION TEST 29
4.2.4 RESULT 30
CONCLUSION 36
REFERENCE 38

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