臺灣博碩士論文加值系統

對單因子的國際資本資產定價模型 (International CAPM) 的研究,可採
(1) 固定風險價格,(2）隨時間改變而變動 (time-varying) 之風險價格的兩種設定。 本文使用多變量 FIGARCH-in-Mean 模型,作為這兩種設定的國際資本資產定價模型之實證模型。FIGARCH (Fractional
Integrated GARCH) 模型是一種用來捕捉具有長期相依或稱緩長記憶效果之波動程度的模型,藉由參數 d , 0<d<1 的引進,可以控制記憶程度的強弱,使得模型在操作上更具彈性。 實證上,本文選用 MSCI 四個最大資本化國家的股票權益指數和全球市場權益指數的資料來估計,實證結果顯示美國、英國和全球權益的波動
都具有緩長記憶的性質,而且英國更是呈現 IGARCH 的現象,
美國、英國、德國與全球權益的相關係數都相當高,代表這些國家股市的走勢與全球市場的走勢有強烈的互動關係 (Co-Movement) ,而相較於使用 GARCH-in-Mean 模型為實證模型的實證結果,我們發現 FIGARCH-in-Mean 模型是較佳的實證模型。

This paper make use of Multivareate FIGARCH-in-Mean Model to be empirical model of International CAPM with constant and time-varying price of risk . FIGARCH model was chacterizied for long-run dependent of volaility by a new paramter d ,which bounded between 0 and 1 ,control the strength of momery . Empirical evidece show us ,we use MSCI equity index data of four capitalized countries -US,UK,Germary and Janpan, volatilities of US,UK and world index were long-momery process (or Fractional Integrated GARCH process) ,especially volatility of UK even represented IGARCH ! Co-movement behavior between US,UK GM and world market were strong and closed ,furthermore , Multivariate FIGARCH-in-Mean is better empirical model than Multivariate GARCH-in-Mean due to comparasion of two empirical outcomes .

第一章 前言
第二章 多變量 GARCH 模型的回顧
第一節 基本設定
第二節 GARCH-in-Mean 在資本資產定價模型的應用
第三節 國際資本資產定價模型的設定
第三章 多變量 FIGARCH-in-Mean 設定的國際資本資產定價模型
第四章 實證分析
第一節 資料描述
第二節 實證結果與分析
第五章 結論與展望
第六章 參考文獻

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