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標題: The Measurements of Value at Risk on TAIEX Futures
作者: 張瑞竹
Chang, Jui-Chu
關鍵字: GARCH;GARCH;Extreme Value Theory;VaR;Back-Testing;極值理論;風險值;回溯測試
出版社: 財務金融系所
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極值理論常被用來研究金融資產尾部極值的行為,本研究考慮台股期貨報酬具有厚尾的特性,在避免低估其風險值下,以極值理論進行風險值的估計,台股期貨報酬還有波動群聚的特性,以AR(1)-GARCH(1,1) 模型來配適其報酬資料,捕捉報酬的條件異質變異,再利用極值理論估計風險值,另外還使用歷史模擬法及RiskMetrics的指數加權移動平均法來估計風險值。
以2006年1月2日至2009年12月31日進行回溯測試來評估模型的正確性,回溯測試期間分為金融風暴發生前及金融風暴期間,結果顯示在金融風暴發生前,三個模型估計的風險值皆可通過驗證;在金融風暴期間,考慮GARCH效果下,再以極值理論模型估計出來的風險值最準確,而歷史模擬法在99% 信賴水準下及較長的移動窗口下的風險值估計較為準確,在95%信賴水準下容易低估風險值,EWMA模型的表現最差,不適合用來估計台股期貨的風險值。

Taking into consideration that the return distribution of TAIEX Futures is fat-tail, this paper adapts Extreme Value Theory to calculate Value-at-Risk. Extreme value theory is powerful to study the behavior of the tail distribution. That the volatility of returns is clustering implies that returns are conditionally heteroskedastic. This study uses AR(1)-GARCH (1,1) model to measure the standardized innovations of returns on application of Extreme Value Theory. This study also implements historical simulation approach and EWMA model of RiskMetrics to measure VaR.
This study exams the accuracy of these VaR models by back-testing and the back-testing sample period is from January 2, 2006 to December 31, 2009, before financial crisis period and during financial tsunami period. Before financial crisis period, the empirical results prove that VaR can be calculated right by these models. During financial tsunami period, VaR can be calculated right by AR(1)-GARCH(1,1)-GEV model. Historical simulation approach may underestimate VaR in 0.95 and 0.99 quantiles. Using RiskMetrics model to evaluate VaR of TAIEX Futures no matter in which confidence interval is not appropriate.
其他識別: U0005-2807201016301600
Appears in Collections:財務金融學系所

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