本篇研究同時考慮解決資產報酬變異隨時間變化的特性與當標的資料分配不符合原始假設的問題。為配合資產報酬變異隨時間變化的特性，通常利用等權移動平均法（SWMA）、一般向量自我迴歸共變異矩陣（GARCH）與指數加權移動平均法（EWMA）等模型來對估計值加以處理。然而，這些方法都是根據樣本的變異數或報酬的共變異數估算的估計值。當原始的標的資料分配不符合假設，則會有估計不具效率的問題。本研究最主要目的在估計這些厚尾高峽峰型態資料之頑強最適避險比率，來驗證台灣股價指數期貨與摩根台灣股價指數期貨並進行動態的避險策略。本研究同時使用條件下等權移動平均法與指數加權移動平均法來進行頑強最適避險比率的估算，在將之與非條件下的個別方法估算出來的估算值進行比較。可以得知頑強最適避險比率估算的避險投資組合變異數比個別方法相對較小，更甚而言之，頑強的最適避險比率所估算的變異數比為避險時所估算的變異數減少相當多的程度，且可在動態避險時大量的減少交易成本。

This article considers solving that conditional distribution of most financial asset return tends to vary over time and the distribution of underlying asset does not conform with ordinary assumption simultaneously. In order to fit time-varying volatility in returns of asset, estimators dealt with simple weighted moving average (SWMA), GARCH, or EWMA models are usually applied. However, these methods are estimated according to sample variance and covariance estimators of returns. When the distribution of underlying asset does not match with the ordinary assumption, the estimators are not in general efficient. The primary purpose in the article is to verify the dynamic hedging strategies in Taiwan stock index futures and MSCI futures by estimating the robust estimation of optimal hedge ratio (OHR) when the data is leptokurtic and fat-tail. This article uses conditional SWMA and EWMA at the same time to estimate the robust estimation of OHR, and compares with the results in unconditional SWMA and EWMA. The variance of hedged portfolio is computed in the robust OHR are less than that in the unconditional way. In addition, the variance of hedged portfolio is computed in the robust OHR are much less than before, thus reducing the transaction costs which produces in dynamic hedging strategies.

第一章  緒  論………………………………………………………………………1	
第一節  研究動機………………………………………………………………1	
第二節  研究目的………………………………………………………………2	
第三節  研究架構………………………………………………………………3
第四節  研究流程………………………………………………………………4	
第二章  文獻回顧……………………………………………………………………5	
第一節  股價指數期貨契約……………………………………………………5	
第二節  台灣股價指數期貨契約………………………………………………8	
第三節  避險理論回顧……………………………………………… ……….11	
第四節  實證相關文獻………………………………………………………..14	
第三章  研究方法…………………………………………………………………..23	
第一節  避險比率的估計……………………………………………………..23	
第二節  等權移動平均法……………………………………………………..24	
第三節  指數移動平均法……………………………………………………..25	
第四節  頑強最適避險比率估計值…………………………………………..28	
第五節  避險績效的衡量……………………………………………………..33	
第四章  實證結果…………………………………………………………………..36	
第一節  資料來源……………………………………………………………..36	
第二節  資料型態……………………………………………………………..38	
第三節  避險比率的估計結果………………………………………………..43	
第四節  避險績效的結果……………………………………………………..45	
第五章  結  論……………………………………………………………………..58	
中文參考文獻………………………………………………………………………..61	
英文參考文獻………………………………………………………………………..62	
	
表次

【表2-1】以台灣股價指數為標的之股價期貨契約………………………………10	
【表4-1】台灣股價指數現貨與期貨價格的基本統計量…………………………40	
【表4-2】台灣股價指數現貨與期貨報酬的基本統計量…………………………41	
【表4-3】MSCI現貨與期貨價格的基本統計量………………………………….41
【表4-4】MSCI現貨與期貨報酬的基本統計量………………………………….42
【表4-5】避險比率和投資組合變異估計結果（台灣股價指數期貨）…………52
【表4-6】不同控制變數下的投資組合變異估計結果（台灣股價指數期貨）…52	
【表4-5】避險比率和投資組合變異估計結果（MSCI）………………………..53	
【表4-6】不同控制變數下的投資組合變異估計結果（MSCI）………………..53	


圖次

【圖1-1】研究流程圖………………………………………………………………..3	
【圖3-1】不同控制變數下之PE分配…………………………………………….32	
【圖3-2】不同分配的厚尾程度……………………………………………………32
【圖4-1】台灣股價指數現貨與期貨價格走勢圖…………………………………38	
【圖4-2】台灣股價指數現貨與期貨報酬…………………………………………38	
【圖4-3】MSCI現貨與期貨價格走勢圖………………………………………….39	
【圖4-4】MSCI現貨與期貨價格………………………………………………….39	
【圖4-5】移動視窗的估計方法圖示………………………………………………44	
【圖4-6】台灣股價指數現貨的避險比率估計結果………………………………50	
【圖4-7】摩根台灣股價指數現貨的避險比率估計結果…………………………51

中文參考摘要
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。

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余尚武、賴昌作（2001），「股價指數期貨之避險比率與避險績效」，管理研究學報，第1卷第1期，頁1-31。

吳方聖（2002），運用條件Power EWMA估計式衡量風險值之績效研究，東吳大學企業管理學研究所。

高 峰（2003） ，跳躍風險之避險策略，淡江大學財務金融研究所碩士論文。

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張哲宇（1997），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企業管理學程碩士論文。

張育達（1991），期貨契約最適避險策略之研究，台灣大學財務金融學研究所。

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