石油价格收益的非高斯性建模

I. Mauleón
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引用次数: 0

摘要

适合多元推广的非高斯密度拟合每日石油价格回报。用描述性和形式化方法对几种估计模型的绝对拟合优度和比较拟合优度进行了评估。为此,介绍了一种新的统计密度预测试验。对估计模型进行广泛的描述和统计分析表明,不对称的Student' t与EGARCH条件方差模型具有显著的良好拟合。该密度的参数在几个子样本上也是稳定的,而其余的模型参数则不是。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling Non Gaussianity of Oil Price Returns
Non Gaussian densities suitable for multivariate generalizations are fitted to daily oil price returns. The absolute and comparative goodness of fit of the several estimated models, is assessed with descriptive and formal methods. A new statistical density forecast test is introduced for that purpose. Extensive descriptive and statistical analysis of the estimated models show that an asymmetric Student' t, with the EGARCH conditional variance model yields a remarkable good fit. The parameters of this density are also stable over several subsamples, while the remaining model parameters are not.
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