Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-01-01 DOI:10.5705/ss.202022.0013

Yaolan Ma, Mo Zhou, Liang Peng, Rongmao Zhang

引用次数: 0

Abstract

Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference Abstract: The stylized fact of heavy tails makes median inferences appealing in ﬁtting an ARMA model with heteroscedastic errors to ﬁnancial returns. To ensure that the model still concerns the conditional mean, we test for a zero mean of the errors using a random weighted bootstrap method for quantifying estimation uncertainty. The proposed test is robust against heteroscedasticity and heavy tails as we do not infer the heteroscedasticity and need fewer ﬁnite moments. Simulations conﬁrm the good ﬁnite sample performance in terms of size and power. Empirical applications caution the model interpretation after using a median inference.

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使用中值推理的ARMA-GGARCH模型的零误差均值检验

中位数推理适用于将具有异方差误差的ARMA模型拟合到财务回报中，因为已知此类回报具有重尾。为了确保模型仍然与条件均值相关，我们使用随机加权自举方法来量化估计不确定性，以检验误差的均值是否为零。所提出的检验对异方差和重尾具有鲁棒性，因为我们不推断异方差，并且需要较少的有限矩。仿真验证了所提出的测试在尺寸和功率方面具有良好的有限样本性能。经验应用表明，我们在使用中位数推理后解释模型时需要谨慎。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.