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研究生:張淑怡
研究生(外文):Shu-Yi Chang
論文名稱:應用OrthogonalGarch與GarchBootstrap模型之風險值模式於國內共同基金之研究
論文名稱(外文):Apply VaR Model from Orthogonal Garch and Garch Bootstrap to the Research of Domestic Mutual Fund
指導教授:黃嘉興黃嘉興引用關係
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:財務金融系碩士班
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:2004
畢業學年度:92
語文別:中文
論文頁數:108
中文關鍵詞:風險值GARCH(1拔靴複製法Orthogonal GARCHGarch Bootstrap
外文關鍵詞:Value-at-Risk(VaR)、GARCH(1Bootstrap Method、Orthogonal Garch、GARCH Bo
相關次數:
  • 被引用被引用:5
  • 點閱點閱:113
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
由於國內對於有關風險值的探討多著墨於股票、債券、匯率等方面,而在共同基金方面相對較少且多為模擬法(如:蒙地卡羅法),在參數解析法上則甚少。故本研究除了嘗試以GARCH(1,1)與拔靴複製法(Bootstrap Method)為評估方法,來改善傳統Delta-Normal法之缺點外,將再納入以往共同基金文獻上鮮少探討的Orthogonal GARCH與條件拔靴法(GARCH Bootstrap)等二種模型,除亦可改善常態分配理論上的缺點,以捕捉實際分配具厚尾的情形外,並加入考量基金投資組合中的各標的資產的因素與修正Bootstrap法未改量資料趨勢之缺點。進而加以比較此四種風險評估模型實證之結果,以期找出較佳的共同基金風險評估模型。
本研究實證結果顯示:相較於常用之GARCH(1,1)、Bootstrap的所估算風險矩陣,Orthogonal Garch與Garch Bootstrap模式對於變異數與共變異數矩陣具有較佳的預測能力,有助於提升VaR的準確性,不過在本研究中這兩種模式間則無法明顯地分出優劣,因此須視投資決策者使用之不同目的而定出不同的方法。故在國內共同基金單變量的風險評估上本研究建議可採用GARCH Bootstrap模式。而若考量其投資組合中的各標的資產之持股情形時,則可採用Orthogonal Garch模式。
在基金績效評比方面,傳統夏普指數分別與修正夏普指數(V1)及風險均考慮標竿市場影響的指標(V2)在績效排名上具有高正相關性;因此,當投資人對風險的定義為下方風險時,則此兩指標適合作為績效評估的標準,意即其可以替代傳統的夏普指數。
Due to domestic investigations are focus more on VaR of stocks, bonds, and foreign exchange, but less on mutual fund. And investigation of mutual fund are more on simulation-based method (ex. Monte Carlo Simulation), but less are on paramentric-based method. Therefore, our research tries to use either GARCH(1,1) and Bootstrap method for estimated method to improve shortcomings of trditonal Delta-Normal method. In addition, our research incorporates Orthogonal GARCH and GARCH Bootstrap model which haven’t explore in past literatures to polish up shortcomings of normal distribution, and to catch the fat tail of the real distribution. And our research includes factors that effects each underlying assets and modified Bootstrap method to improve the shortcomings of trends of data. Finally, we compares empirical results of these four kind of VaR methods to find out better mutual fund VaR model.
Empirical results of our research show that to compare with the risk matrixs which GARCH(1,1) and Bootstrap method estimated, Orthogonal Garch and Garch Bootstrap method have better forecasting ability to variance and covariance matrix, and help to improve the precision of VaR. But in our research, we can’t exactly tell which is better. So, different methods choosing must depend on the different purposes of investment deciders. Accordingly, we suggest that in domestic mutual fund’s risk measurement, we can make use of GARCH Bootstrap method. And when take the distributions of each underlying assets in the portfolios into account, we can adopt Orthogonal Garch method.
In the respect of performance rating of mutual fund, traditional Sharp Index are highly related with both modified Sharpe Index(V1) and BRVaR(V2); therefore, when the definition of risk of investor is downside risk, both indicators(V1 and BRVaR(V2)) can substitute for traditional Sharpe Index.
目 錄

中文摘要 ----------------------------------------------------------------------------------------------------- i
英文摘要 ----------------------------------------------------------------------------------------------------- ii
誌謝 -------------------------------------------------------------------------------------------------------------iii
目錄 -------------------------------------------------------------------------------------------------------------iv
表目錄 --------------------------------------------------------------------------------------------------------- v
圖目錄 ---------------------------------------------------------------------------------------------------------vi
第一章 緒論 -------------------------------------------------------------------------------------- 1
第一節 研究動機與目的 ------------------------------------------------------------------ 1
第二節 研究架構 ------------------------------------------------------------------------------ 6
第二章 文獻探討 ------------------------------------------------------------------------------ 7
第一節 風險值(VaR)之介紹 ------------------------------------------------------------- 7
第二節 風險值相關文獻 ------------------------------------------------------------------12
第三章 研究方法 ------------------------------------------------------------------------------25
第一節 資料檢驗與處理 ------------------------------------------------------------------27
第二節 風險值評估模型之建構 ------------------------------------------------------32
第三節 VaR的計算方式 ------------------------------------------------------------------46
第四節 風險值之驗證 ----------------------------------------------------------------------48
第五節 基金績效評估指標 --------------------------------------------------------------53
第四章 實證研究 ------------------------------------------------------------------------------57
第一節 資料採樣與來源 ------------------------------------------------------------------58
第二節 資料檢驗 ------------------------------------------------------------------------------60
第三節 風險值模型估計 ------------------------------------------------------------------67
第四節 風險值模型準確度之驗證 --------------------------------------------------82
第五節 基金績效評估實證結果 ------------------------------------------------------88
第五章 結論與建議 --------------------------------------------------------------------------92
第一節 結論 --------------------------------------------------------------------------------------92
第二節 後續研究建議 ----------------------------------------------------------------------96
參考文獻 ------------------------------------------------------------------------------------------------------97

表目錄

表1 基金家數、個數與規模統計表 ---------------------------------------------------- 3
表2 研究對象 ---------------------------------------------------------------------------------------58
表3 共同基金週報酬率敘述統計表 ----------------------------------------------------60
表4 Lilliefors 檢定結果表 -------------------------------------------------------------------62
表5 ADF 單根檢定法之結果 --------------------------------------------------------------64
表6 ARCH效果的檢定結果表 ------------------------------------------------------------66
表7 單變量AR(1)-GARCH(1,1)模型參數估計 -----------------------------------68
表8 單變量AR(1)-GARCH(1,1)模型參數估計之分析 -----------------------69
表9 特徵值分析 ----------------------------------------------------------------------------------- 71
表10 Orthogonal GARCH(1,1)模型參數估計 --------------------------------------- 73
表11 Orthogonal GARCH(1,1)模型參數估計之分析 ----------------------------77
表12 回溯測試法與Z-Score之評估結果 --------------------------------------------- 85
表13 概似比檢定之評估結果 ----------------------------------------------------------------87
表14 股票型共同基金排名 --------------------------------------------------------------------90
表15 股票債券平衡型一般股票型基金排名 -----------------------------------------91
表16 Spearman相關檢定 -----------------------------------------------------------------------91


圖目錄

圖1 風險值 ------------------------------------------------------------------------------------------------ 8
圖2 研究流程圖 ----------------------------------------------------------------------------------------26
圖3 移動視窗示意圖 --------------------------------------------------------------------------------49
圖4 元大多元基金報酬率機率分配圖 -----------------------------------------------------63
圖5 比較各模型總穿越次數直方圖 ---------------------------------------------------------86
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