A conditional-SGT-VaR approach with alternative GARCH models
A conditional-SGT-VaR approach with alternative GARCH models
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DOI：
10.1007/s10479-006-0118-4
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发表时间：
2007-04-01
影响因子：
4.8
通讯作者：
Theodossiou, Panayiotis
中科院分区：
文献类型：
--
作者：
Bali, Turan G.;Theodossiou, Panayiotis
本文提出了一种基于偏态广义t分布的VaR估计和预期缺口度量的条件技术。收益的条件均值和条件方差的估计是基于GARCH模型的十种流行的变体。结果表明，TS-GARCH和EGARCH模型具有最好的整体性能。其余的GARCH规范，除了少数情况外，都会产生可接受的结果。无条件SGT-VaR在样本内评估上表现良好，但在样本外评估上未通过测试。后者表明，在计算VaR和预期缺口指标时，需要纳入时变的平均值和波动率估计。
This paper proposes a conditional technique for the estimation of VaR and expected shortfall measures based on the skewed generalized t (SGT) distribution. The estimation of the conditional mean and conditional variance of returns is based on ten popular variations of the GARCH model. The results indicate that the TS-GARCH and EGARCH models have the best overall performance. The remaining GARCH specifications, except in a few cases, produce acceptable results. An unconditional SGT-VaR performs well on an in-sample evaluation and fails the tests on an out-of-sample evaluation. The latter indicates the need to incorporate time-varying mean and volatility estimates in the computation of VaR and expected shortfall measures.