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研究生:徐珮雅
研究生(外文):Pei-Ya She
論文名稱:不同市場趨勢中雜訊對避險績效之影響
論文名稱(外文):The Effects of Nose on Index Hedge Performance
指導教授:吳如萍吳如萍引用關係
學位類別:碩士
校院名稱:樹德科技大學
系所名稱:金融與風險管理系碩士班
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:50
中文關鍵詞:避險績效、避險比率、雜訊、GARCH
外文關鍵詞:hedging performancehedge rationoiseGARCH
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股價指數期貨避險比率之估計與應用,為市場股票投資者進行避險策略之重要依據,而期貨與現貨市場中各自之雜訊可能影響避險比率之估計及績效,因此,本研究以兩日平均報酬率作為去除雜訊的代理變數,利用NAÏVE模型、OLS模型、ECM模型及GARCH模型三種避險策略,分別對期貨與現貨市場中之原始報酬率資訊與去除雜訊之兩日移動平均數之資訊進行避險比率之估計,樣本則以台灣期貨交易所中,交易量最大的四項期貨商品,亦即台灣加權股價指數期貨、電子類股指數期貨、金融類股價指數期貨及小型台股指數期貨分別加以實證。
結果顯示,四項商品使用二日平均數估計之避險比率,不論利用何種模型,均較單日報酬所估之避險比率為高,因此在去除雜訊後,提高期貨與現貨之彼此相關性,而在避險績效之表現中,在2007及2008年市場呈現較平穩之股價走勢時,未去除雜訊的單日報酬率所表現之每日動態避險基績效較佳,然在2009及2010年,市場價格大幅下降及上升的趨勢中,此四項商品,除NAÏVE方法外,其餘模型均以去除雜訊後之績效為佳,而NAÏVE模型表現之績效未較GARCH、OLS及ECM為佳,因此,在市場盤整期間,波動較低時,以傳統之全含資訊進行避險策略,但在市場大幅波動及上升或下降趨勢中,雜訊確實干擾避險策略之運作,則應採兩日平均值,去除雜訊後之訊息進行避險策略。


Estimation and application of hedging ratio in stock index futures are important foundations for stock investors in implementing hedging strategies. Noise in futures and spot markets may affect the estimation and performance of hedge ratios. Thus, this study uses two-day average returns as the proxy variable for removing noise, with the three hedging strategies of NAÏVE model, OLS, model, ECM model and GARCH model to conduct hedge ratio estimation for the raw returns information of the futures and spot markets and for the two-day average movement of noise removal. The samples are empirically verified using TAIFEX Futures, Electronic Sector Index Futures, Finance Sector Index Futures, and Small Cap Index Futures, which are the four futures products with greatest trading volume in the Taiwan Futures Exchange.
Results show that when using the hedge ratio of two-day averages for the four products, every model were higher than the hedge ratios estimated with single-day returns. Therefore, after removing noise, the correlation between futures and spot markets are elevated. Hedging performance in 2007 and 2008 with more stable stock trends, single-day returns without noise removal had better daily dynamic hedge fund performance. However, in 2009 and 2010 with volatile rises and falls in the market prices, for these four products, models other than the NAÏVE method had better performance after noise removal. The performance of the NAÏVE model was not as good as GARCH, OLS, and ECM. Thus, during periods of market correction, when there is lower volatility, traditional comprehensive information should be used for hedging strategy, but when the market is volatile or in a rising or falling trend, noise can indeed interfere with the operations of hedging strategies. In this case, one should use two-day averages to remove noise to conduct hedging strategies.


中文摘要 I
英文摘要 II
誌謝 III
目錄 IV
圖目錄 V
一、緒論 1
1.1研究背景與動機 1
1.2研究方法 2
1.3研究架構 3
2.1股價影響因素 5
2.2雜訊交易理論 6
2.3股價指數期貨 10
2.4避險理論 16
三、研究方法 27
3.1數列檢定 27
3.1.1單根檢定 27
3.2避險模型 29
3.2.1傳統避險理論 29
3.2.2簡單線性迴歸模型(OLS) 29
3.2.3誤差修正模型(error correction model, ECM) 30
3.2.4Bivariate GARCH模型 31
3.3避險績效之衡量 33
四、實證研究 34
4.1資料來源及處理 34
4.2樣本敘述統計 37
4.3各種避險模型之避險比率 38
4.4避險績效 41
五、結果與建議 44
參考文獻 45



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