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研究生:李奇潭
研究生(外文):Chi-Tan Lee
論文名稱:在平穩與波動市場下之風險值估算-應用對稱與不對稱GARCH模型
論文名稱(外文):Value-at-Risk Calculation in Tranquil and Volatile Markets Using Symmetric and Asymmetric GARCH Models.
指導教授:許文彥許文彥引用關係
指導教授(外文):Wen-Yen Hsu
學位類別:碩士
校院名稱:逢甲大學
系所名稱:財務金融學所
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:2005
畢業學年度:93
語文別:中文
論文頁數:62
中文關鍵詞:回溯測試波動性估計風險值GARCH厚尾
外文關鍵詞:GARCHVolatility forecastingFat-tailBack testingValue-at-Risk
相關次數:
  • 被引用被引用:2
  • 點閱點閱:308
  • 評分評分:
  • 下載下載:51
  • 收藏至我的研究室書目清單書目收藏:1
隨著2006 年第二巴塞爾資本協定(BASEL II)即將實行,金融業界皆已開始試圖發展其內部的風險控管模型。針對市場風險,第二巴塞爾資本協定已經開放金融業界自行開發其內部風險值模型。以往對於風險值的研究往往專注於風險值模型的修正,且使用實際資料估算其正確度,並以此做為風險值的預測模型。但隨著金融環境的改變,風險值預測模型是否會因此產生變化是令人懷疑的。
本文將針對標準普爾500 工業指數(S&P 500)與Datastream Benchmark美國政府公債指數為研究標地,且使用近年來普遍運用於估算金融商品波動性的GARCH 模型與其變化模型,再加入了不對稱波動性預估模型與傳統的固定波動性模型去評估風險值的衡量準確度,透過觀察時期的改變去尋找在各個時期下的風險值預測模型,探討風險值預測模型是否存在著穩定性。結果發覺,在95%的信心水準下風險值預測模型具有穩定性的情
況。但對於99%信心水準而言,穩定性並不存在。
The study wants to find out whether we can always use the same VaR model to control market risk? A number of estimates based on symmetric and asymmetric GARCH models and constant variance models are examined. Two financial indexes are used: US S&P 500 stock index and Datastream Benchmark US Treasury Bond index. The back tests are performed to calculate average violation rate in three-, five-, and ten-years period based on one quarter moving window. The results show that the EWMA model is superior among the time-variant and time-independent variance models under 95% confident interval. However, under 99% confident interval, no model consistently outperforms others, suggesting that the performance of VaR models in terms of controlling market risk may not be stable under 99% confident interval. The finding is particularly important since the VaR for market risk under Basel II is calculated based on 99% confident interval.
第一章 緒論···································································1
第一節 研究背景與動機·························································1
第二節 研究目的·······························································2
第二章 文獻回顧······························································ 4
第三章 研究方法······························································ 8
第一節 樣本選取與風險值準確度估算方法·········································8
第二節 風險值估算方法························································10
第三節 波動性估算方法························································11
第四章 實證結果······························································17
第一節 樣本敘述······························································17
第二節 實證結果······························································23
第五章 結論··································································42
參考文獻·····································································44
附錄·········································································47
張文華、王家真、吳壽山,風險值方法比較,證券市場發展季刊,139-161,2000。
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