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研究生:賴廷偉
研究生(外文):Lai, Tin-Wei
論文名稱:基差平緩化動態避險策略─卡曼過濾預測模型之應用
論文名稱(外文):Basis Flattening Dynamic Hedging Strategy- An Application of Kalman Filter Forecasting Model
指導教授:李進生李進生引用關係盧陽正盧陽正引用關係
指導教授(外文):Lee, Chin-ShenLu, Yang-Cheng
學位類別:碩士
校院名稱:銘傳大學
系所名稱:金融研究所
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:1997
畢業學年度:85
語文別:中文
論文頁數:83
中文關鍵詞:基差平緩化動態避險策略
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  本研究之目的為構建基金差平緩化動態避險模型,使得避險投資組合的風險最小化。本研究利用金融工程衍生性商品合成的觀念重新定義基差值,並結合卡曼過濾預測模型預測避險投資組合之條件期望值,使得避險投資組合的價值會因為基差值的平緩化而不存在任何的超額風險貼水,從而趨近於完美避險的境界。
  在本研究的研究設計方面,基差平緩化避險模型規避了靜態避險模型中與真實市場不符的問題,以及GARCH避險模型利用價格差分值進行實證研究所可能發生的資訊漏損之問題,所以採用完整價格水準資訊實證研究,並以雙變量GARCH避險模型為對照組以求取更精準的實證結果。
  本研究利用1987年12月1日1996年5月31日的期間內三大類十一種期貨契約研究對象。實證結果為在至曼過濾預測模型準確地預測之下,本研究的避險模型估計所得之動態避險比例波動幅度明顯地小於雙變量GARCH避險模型,此種現象表示雙變量GARCH避險模型之交易成本將較基差平緩化避險模型高出許多;在避險績效的比較上,基差平緩化避險模型亦顯著地優於雙變量GARCH避險模型;再者,在最適避險期間的選取上,基差平緩化避險模型不論是以何種期貨契約所得到之結果均以一年期為最適避險期間,相較雙變量GARCH避險模型不確定最適避險期間的長度而言,將使得避險者在避險期間的選取上有一定的依據。
  The purpose of this study is to develop a basis stabilizing dynamic hedging model, which minimize the risk of hedging portfolio. The concept of synthetic financial derivatives in Financial Engineering to redefine the basis of hedge portfolio, or target basis. The Kalman Filter Forecasting model is used to forecast conditional expected value of the hedge portfolio. Under basis stabilizing dynamic hedging model, the basis of hedging portfolio value will exist no abnormal risk premium and approach to perfect hedge due to the flattening basis.
  In order to minimize the risk, the variation of the hedge portfolio is controlled to be stable in this research. Resultantly, any abnormal risk premium is eliminated. The risk of the hedged portfolio approximate zero finally. In our research design, we aviod the problem of unreality in static hedging model and problem of the information loss due to price differencing. We use price level to insure that all available information is contained. The bivariate GARCH hedging model acts as the control group.
  For empirical, 11 furures contracts from 3 groups in Untied States during period of December 1st 1987 to May 31st 1996 is selected. The result shows that hedge ratios from our basis stabilizing dynamic hedging model is more stable then that of the bivariate GARCH hedging model. This implies the transaction cost in bivariate GARCH hedging model. is higher then our hedging model. From the hedging effectiveness point of view, no matter hedging period is one year, six months or three months, basis stabilizing dynamic hedging model is much better then the bivariate GARCH hedging model. Moreover, no matter what futures contract is selected, the optimun hedging period in basis stabilizing dynamic hedging model is one year. In the bivariate GARCH hedging model hedgers are not aware of what frequency of hedging should be employed to approach optimum.
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