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研究生:黃俊諺
研究生(外文):Chun-Yen Huang
論文名稱:台灣股價指數報酬高階動差之實證分析-SU-Normal分配之應用
指導教授:李偉銘李偉銘引用關係
指導教授(外文):Wei-Ming Lee
學位類別:碩士
校院名稱:國立中正大學
系所名稱:國際經濟所
學門:社會及行為科學學門
學類:經濟學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:53
中文關鍵詞:型態參數高階動差GARCH 模型
相關次數:
  • 被引用被引用:2
  • 點閱點閱:239
  • 評分評分:
  • 下載下載:43
  • 收藏至我的研究室書目清單書目收藏:0
早期資產報酬分析常假設條件變異數固定與常態分配, 然而此設定無法完全解釋資產報酬的特性。
雖然利用 ARCH 與 GARCH 等模型能允許條件變異數隨時間變化而解決波動聚集現象的問題,
但架構在常態分配假設下之模型, 相對忽略了偏態與厚尾等資料特性, 因此放寬分配假設並考量高階動差之影響遂成為往後重要研究議題。
Choi and Nam(2008) 以傳統 GARCH 模型搭配 SU-normal 分配, 用以探討匯率與股價報酬, 但其僅對型態參數做固定假設,
且未考慮波動不對稱之效果。
因此本文設定傳統 GARCH-M 模型與 GJR-GARCH-M 模型搭配常態與 SU-normal 分配,
探討台灣加權股價指數條件波動行為與高階動差之影響。 資料期間由 2001 年 1 月 2 日至 2008 年 6 月 30 日的日資料與週資料進行分析。
實證結果顯示我國股價波動除了具有異質性外, SU-normal 分配假設下, 並無波動不對稱現象, 不同於常態分配假設下之實證結果。
且台股報酬均呈現負偏及超額峰態的特性, 日資料之峰態特性與週資料之偏態與峰態特性均會隨時間而變。
在考慮了 moment-in-mean 之設定下, 本研究認為無論日資料亦或週資料,
GARCH-M-in-M-SU(time varying) 模型最能解釋台灣股價指數之動態行為。
1 緒論
1.1 研究動機與目的
1.2 論文架構

2 文獻回顧
2.1 條件變異數的文獻探討
2.2 非常態分配的文獻探討
2.3 針對國內股價指數報酬的文獻探討

3 計量方法
3.1 理論模型
3.2 模型相關檢定
3.2.1 單根檢定
3.2.2 序列自我相關檢定
3.2.3 異質性檢定

4 資料與實證結果
4.1 資料介紹、來源與處裡
4.2 實證模型
4.3 日資料結果分析
4.4 週資料結果分析

5 結論與建議
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