英文文献：Autoregressive Conditional Heteroskedasticy Under Error-Term Non-Normality-错误项非正态下的自回归条件异方差
英文文献作者：Ramirez, Octavio A.
英文文献摘要：
This paper explores the impact of error-term non-normality on the performance of the normal-error Generalized Autoregressive Conditional Heteroskedastic (GARCH) model under small and moderate sample sizes. A non-normal-, asymmetric-error GARCH model is proposed, and its finite-sample performance is evaluated in comparison to the normal-error GARCH under various underlying error-term distributions. The results suggest that one must be skeptical of using the normal-error GARCH when there is evidence of conditional error-term non-normality. The conditional distribution of the error-term in a previous mainstream application of the normal GARCH is found to be non-normal and asymmetric. The same application is used to illustrate the advantages of the proposed non-normal-error GARCH model.

摘要本文探讨了在小样本和中等样本容量下，误差项非正态性对正态误差广义自回归条件异方差模型性能的影响。摘要提出了一种非正态、非对称误差GARCH模型，并将其有限样本性能与不同误差项分布下的正态误差GARCH进行了比较。结果表明，当有条件误差项非正态性的证据时，人们必须对使用正态误差GARCH持怀疑态度。在正规GARCH的早期主流应用中，发现错误项的条件分布是非正规的和不对称的。同样的应用也说明了所提出的非正态误差GARCH模型的优点。