教師資料查詢 | 類別: 期刊論文 | 教師: 鄭婉秀 WAN-HSIU CHENG (瀏覽個人網頁)

標題:Skewness and Leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns
學年99
學期1
出版(發表)日期2011/01/01
作品名稱Skewness and Leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns
作品名稱(其他語言)考量偏態與厚尾之GRACH型態風險值估計於石油與金屬資產之應用
著者Cheng, Wan-hsiu; Hung, Jui-cheng
單位淡江大學財務金融學系
出版者Amsterdam: Elsevier BV * North-Holland
著錄名稱、卷期、頁數Journal of Empirical Finance 18(1), pp.160-173
摘要This paper utilizes the most flexible skewed generalized t (SGT) distribution for describing petroleum and metal volatilities that are characterized by leptokurtosis and skewness in order to provide better approximations of the reality. The empirical results indicate that the forecasted Value-at-Risk (VaR) obtained using the SGT distribution provides the most accurate out-of-sample forecasts for both the petroleum and metal markets. With regard to the unconditional and conditional coverage tests, the SGT distribution produces the most appropriate VaR estimates in terms of the total number of rejections; this is followed by the nonparametric distribution, generalized error distribution (GED), and finally the normal distribution. Similarly, in the dynamic quantile test, the VaR estimates generated by the SGT and nonparametric distributions perform better than that generated by other distributions. Finally, in the superior predictive test, the SGT distribution has significantly lower capital requirements than the nonparametric distribution for most commodities.
關鍵字Skewed generalized t distribution; Volatility; Value-at-Risk
語言英文
ISSN0927-5398
期刊性質國外
收錄於SSCI
產學合作
通訊作者Cheng, Wan-hsiu
審稿制度
國別荷蘭
公開徵稿
出版型式紙本
相關連結
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