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研究生:盧羿安
研究生(外文):Yi-an Lu
論文名稱:金融市場結構轉換次數的偵測
論文名稱(外文):Detectiong numbers of switching change in financial markets
指導教授:傅承德傅承德引用關係
指導教授(外文):Cheng-der Fuh
學位類別:碩士
校院名稱:國立中央大學
系所名稱:統計研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:38
中文關鍵詞:結構轉換希伯特黃轉換
外文關鍵詞:regime switchingHHT
相關次數:
  • 被引用被引用:2
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  • 下載下載:42
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本文旨在利用 Huang et al. (1998) 所提出的一經驗法則-希伯特-黃轉換 (Hilbert-Huang transform,HHT) 分析方法-對一時間區間內之股價結構轉換 (regime switch) 的次數做一判斷。一般熟知經濟體制顯示其偶爾會從一個結構 (regime) 跳到另一個。一個國家的經濟,週期性地從膨脹轉換 (switch) 到緊縮而後再轉換回去。而一金融市場也會週期性地從低波動 (low-volatility) 轉換到高波動 (high-volatility) 的結構而後再轉換回去。模擬的結果發現,變動的形式為波動變動 (volatility shift) 時,其判斷轉換的時間點較趨勢變動 (drift shift) 來的精準;實證的部分採用臺指 50,並以美國次級房屋信貸風暴為時間區間,對此段時間內判斷出有四次結構轉換。
The purpose of this thesis is to utilize an empirical rule, Hilbert-Huang transform (HHT) proposed by Huang et al. (1998), to determine numbers of regime switching on the stock in a time interval. It is well known that economic systems exhibit occasional jumps from one regime to another. A nation’s economy periodically switches from expansion to contraction and back again, and the dynamics differ between these two regimes. A financial market periodically switches from a low-volatility regime to a high-volatility regime and back again. Simulation result shows that the time period of switching of volatility shift determined by HHT is more accurate than the time period of switching of drift shift. Empirically, we adopt Taiwan 50 index at the event of the U.S. subprime mortgage, and we get that there are four regime switching in this time period.
目錄
中文摘要 ………………………………………………………………… i
英文摘要 ………………………………………………………………… ii
誌謝   ………………………………………………………………… iii
目錄   ………………………………………………………………… iv
第一章 序論 …………………………………………………………… 1
    1.1 研究目的 …………………………………………………… 1
    1.2 文獻回顧 …………………………………………………… 3
第二章 研究方法 ……………………………………………………… 5
    2.1 瞬時頻率 (instantaneous frequency) ……………………… 5
    2.2 經驗模態分解法 (The Empirical Modes Decomposition
      method,EMD) ……………………………………………
6
    2.3 希伯特能譜分析 (The Hilbert spectral analysis) ………… 11
第三章 模擬 …………………………………………………………… 13
    3.1 判斷法則 …………………………………………………… 13
    3.2 趨勢變動 (drift shift) …………………………………… 14
      3.2.1 常態分配 (normal distribution) …………………… 14
      3.2.2 幾何布朗運動 (geometric Brownian motion) ……… 17
      3.2.3 馬可夫轉換模型 (Markov switching model) ……… 19
    3.3 波動變動 (volatility shift) ………………………………… 21
      3.3.1 常態分配 (normal distribution)  …………………… 21
      3.3.2 幾何布朗運動 (geometric Brownian motion) ……… 24
      3.3.3 馬可夫轉換模型 (Markov switching model) ……… 26
第四章 實證研究 ……………………………………………………… 28
第五章 結論 …………………………………………………………… 33
參考文獻 ………………………………………………………………… 34
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