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題 名 | Value-at-Risk Forecasts in U.S. Crude Oil Markets=美國原油市場之風險值預測 |
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作 者 | 蘇榮斌; | 書刊名 | 中華科技大學學報 |
卷 期 | 42 2010.01[民99.01] |
頁 次 | 頁161-175 |
分類號 | 554.68 |
關鍵詞 | 風險值; 自我迴歸條件跳躍強度; 一般化偏態誤差分配; 複合辛普森規則; Value-at-risk; ARJI; SGED; Composite Simpson's rule; |
語 文 | 英文(English) |
中文摘要 | 本研究係使用複合辛普森數值方法求一般化偏態誤差分配(SGED)之下方百分位值,再使用ARJI-N與ARJI-SGED 模型來分別對布倫特與西德州原油之日資料進行一天期風險值之估計與預測。實證結果顯示,布倫特原油呈現微左偏然而西德州原油呈現微右偏,因此對布倫特原油(西德州原油)言,ARJI-SGED (ARJI-N)模型有較佳樣本外風險值預測性能。這些發現說明當金融資產之報酬率呈現左偏時,可捕捉偏態與峰態之一般化偏態誤差分配分配在樣本外風險值預測扮演重要的角色。 |
英文摘要 | This investigation applies a composite Simpson’s rule, a numerical integral method, for estimating quantiles on the skewed generalized error distribution (SGED). Daily spot prices of Brent and WTI crude oil are used as data to examine the one-day-ahead VaR forecasting performance of the ARJI-N and ARJI-SGED models. Empirical results show that Brent (resp. WTI) crude oil exhibits slightly skewed to the left (resp right). Therefore the ARJI-SGED (resp. ARJI-N) model performs the better out-of-sample VaR performance for Brent (resp WTI) crude oil These findings demonstrate that the use of SGED distribution, which explicitly accommodates both skewness and kurtosis, is essential for out-of-sample VaR forecasting when the returns of financial assets exhibit skewed to the left. |
本系統中英文摘要資訊取自各篇刊載內容。