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研究生:張巧薇
研究生(外文):CHANG, CHIAO-WEI
論文名稱:探討具狀態轉換之動態避險模型最小變異避險比率的避險績效
論文名稱(外文):A Discussion on the Hedge Performance of the Minimum Variance Dynamic Hedge Ratio Model with Markov Switching
指導教授:李孟峰李孟峰引用關係
指導教授(外文):LI,MENG-FENG
口試委員:李美杏吳庭斌李孟峰
口試委員(外文):LI,MEI-HSINGWU,TING-PINLI,MENG-FENG
口試日期:2013-06-27
學位類別:碩士
校院名稱:國立臺北大學
系所名稱:統計學系
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:2013
畢業學年度:101
語文別:中文
論文頁數:42
中文關鍵詞:避險模型向量自我回歸模型動態條件相關模型馬可夫狀態轉換避險績效
外文關鍵詞:hedging modelsvector autoregression modeldynamic conditional correlation modelMarkov regime switchingminimum variance hedge ratiohedge performance
相關次數:
  • 被引用被引用:2
  • 點閱點閱:365
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  • 下載下載:42
  • 收藏至我的研究室書目清單書目收藏:0
全球化金融市場提供大眾很多的投資管道,但相對的也使投資人暴露在更多金融市場波動的潛在風險中;尤其是台灣的金融市場更是容易受到國內外政經情勢的波動,而存在更高的投資風險。風險的種類可分為系統性風險和非系統性風險,其中非系統風險可以藉由多角化投資來分散,但是系統風險主要來自於總體經濟狀況或政治因素的改變,必須利用衍生性金融商品將系統性風險移轉給市場上願意承擔風險的投機者。
為了滿足投資人規避金融資產價格波動風險的需求,市場推出選擇權與期貨的衍生性金融商品,使投資人能夠利用現貨與衍生性商品的價格變動的高相關性,進行避險操作,作為投資者的一個良好避險工具。本研究主要利用台灣加權指數現貨及期貨之間的相關性,建立具馬可夫狀態轉換之向量自我回歸模型與動態條件相關GARCH模型,計算每個模型在不同狀態下的避險比率。最後,再依據兩模型的避險比率,評估兩種避險模型的避險績效之優劣。

Nowadays, there are many financial commodities provided by several globalized financial markets. In the meantime, the volatility of financial market also causes a relative of the investor exposure to potential risk. The financial market in Taiwan is especially vulnerable to the disturbance of national and/or international political and economic situation which will conducts a higher investment risk. The types of risk can be divided into systemic risk and non-systematic risk. Non-systematic risk can be diversification by diversifying investment. The system risk is primarily attributed to general economic and political situation. To avoid the system risk, investors may use derivatives to divert the risk to the adventurers.
In order to offer the demand of investors to avoid the price volatility of financial assets, some derivatives such as options and futures are also provided by the market. The high correlation of price variations between spots and derivatives can be applied to the hedge operation and the derivatives will be good hedging instruments for stock investors. This research mainly applies the correlation between spots and futures of Taiwan Weighted Index to establish a vector autoregression model and a dynamic conditional correlation GARCH model with Markov regime switching. The hedge ratios of each model at different regimes are also calculated. Finally, the hedging performances of two hedge models were compared according to the hedge ratios.

目錄
目錄 i
圖目錄 iii
表目錄 iv
第 1 章 緒論 1
1.1研究動機 1
1.2研究目的 2
1.3研究架構 3
第 2 章 文獻回顧 4
2.1避險理論 4
2.2動態避險模型 5
2.3馬可夫狀態轉換模型 7
2.4向量自我回歸模型 7
2.5動態條件相關一般化自我迴歸條件異質模型 8
2.6具馬可夫狀態轉換的模型 10
第 3 章 研究方法 12
3.1平穩時間序列與單根檢定 12
3.2一般自我迴歸條件異質模型 13
3.3固定條件相關一般化自我迴歸條件異質模型 15
3.4動態條件相關一般化自我迴歸條件異質模型 16
3.5向量自我迴歸模型 18
3.6馬可夫狀態機率演算法 19
3.7具馬可夫狀態轉換的時間序列模型 21
3.7.1馬可夫狀態轉換動態條件相關一般化自我迴歸條件異質模型 21
3.7.2馬可夫狀態轉換向量自我回歸模型 23
3.8最小變異避險比率與避險績效 23
3.8.1最小變異避險比率 23
3.8.2避險績效的衡量 24
第 4 章 實證結果與分析 26
4.1資料來源 26
4.2資料變數與處理 26
4.3資料分析 27
4.3.1 基本統計量 27
4.3.2單根檢定 27
4.4 VAR與MSVAR模型比較 28
4.4.1模型選取 28
4.4.2參數估計 29
4.4.3VAR(2)與MS-VAR(1)的避險比率與避險績效比較 30
4.4.4MS-VAR模型轉換之狀態區間探討 31
4.5 DCC GARCH與MS-DCC GARCH模型比較 32
4.5.1DCC GARCH與MS-DCC GARCH參數估計 32
4.5.2DCC GARCH與MS-DCC GARCH的避險比率與避險績效比較 34
4.5.3 DCC GARCH模型與MS-DCC GARCH模型之條件變異數探討 35
4.5.4 MS-DCC GARCH模型轉換之狀態區間探討 35
4.6 狀態轉換模型的避險策略 37
第 5 章 結論 38
參考文獻 39

圖目錄
圖 4 1 MS-VAR(1)模型狀態一的區間 31
圖 4 2DCC GARCH模型與MS-DCC GARCH模型的動態避險比率比較 35
圖 4 3 DCC GARCH、MS-DCC GARCH模型台灣加權股價指數期貨之條件變異數 36
圖 4 4 DCC GARCH、MS-DCC GARCH模型台灣加權股價指數現貨之條件變異數 36
圖 4 5 MS-DCC GARCH模型狀態一的區間 37


表目錄
表 4 1台灣加權股價指數期貨、現貨報酬基本統計量 27
表 4 2台灣加權股價指數期貨、現貨報酬之單根檢定結果 28
表 4 3VAR模型與MSVAR模型落後期數SBC值 28
表 4 4VAR(2)模型與MS-VAR(1)模型的參數估計 30
表 4 5VAR(2)模型與MS-VAR(1)模型的避險比率與避險績效 31
表 4 6DCC GARCH模型與 MS-DCC GARCH模型的參數估計 33
表 4 7DCC GARCH模型與MS-DCC GARCH模型的避險比率與避險績效 35
表 4 8觀察高波動極低波動狀態下個別區間內的避險比率 37

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