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A discussion on the robustness of conditional heteroskedasticity models: Simulation evidence and applications of the crude oil returns
Finance Research Letters ( IF 7.4 ) Pub Date : 2021-04-08 , DOI: 10.1016/j.frl.2021.102053
Yanlin Shi

This paper discusses the inherent robustness of the generalized autoregressive score (GAS) model, such that consistent estimators can still be obtained when large outliers do exist. A recent example includes the historical-writing negative price of the West Texas Intermediate (WTI) crude oil future in early-2020. Via simulation studies, we demonstrate that GAS can produce much more robust estimates than the popular GARCH model. Empirical analysis using the WTI returns over 2017–2020 further supports the superiority of GAS over GARCH models.



中文翻译:

条件异方差模型的稳健性探讨:原油收益的模拟证据与应用

本文讨论了广义自回归评分 (GAS) 模型的内在稳健性,以便在确实存在大的异常值时仍然可以获得一致的估计量。最近的一个例子包括 2020 年初西德克萨斯中质原油 (WTI) 原油期货的历史负价格。通过模拟研究,我们证明 GAS 可以产生比流行的 GARCH 模型更可靠的估计。使用 2017-2020 年 WTI 回报的实证分析进一步支持 GAS 优于 GARCH 模型。

更新日期:2021-04-08
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