淡江大學機構典藏:Item 987654321/72554
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    题名: Skewness and Leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns
    其它题名: 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
    作者: Cheng, Wan-hsiu;Hung, Jui-cheng
    贡献者: 淡江大學財務金融學系
    关键词: Skewed generalized t distribution;Volatility;Value-at-Risk
    日期: 2011-01
    上传时间: 2011-10-24 10:33:19 (UTC+8)
    出版者: Amsterdam: Elsevier BV * North-Holland
    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.
    關聯: Journal of Empirical Finance 18(1), pp.160-173
    DOI: 10.1016/j.jempfin.2010.05.004
    显示于类别:[財務金融學系暨研究所] 期刊論文

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