Matrix GARCH model: Inference and application*

IF 3 1区数学 Q1 STATISTICS & PROBABILITY

Journal of the American Statistical Association Pub Date : 2024-10-18 DOI:10.1080/01621459.2024.2415719

Cheng Yu, Dong Li, Feiyu Jiang, Ke Zhu

引用次数: 0

Abstract

Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financi...

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矩阵 GARCH 模型：推理与应用*

矩阵变量时间序列数据在应用中非常普遍。然而，目前还没有人尝试研究它们的条件异方差性，而这种异方差性在经济和金融领域中经常出现。

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

Journal of the American Statistical Association 数学-统计学与概率论

CiteScore

7.50

自引率

8.10%

发文量

168

审稿时长

12 months

期刊介绍： Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods in economic, social, physical, engineering, and health sciences. Important books contributing to statistical advancement are reviewed in JASA . JASA is indexed in Current Index to Statistics and MathSci Online and reviewed in Mathematical Reviews. JASA is abstracted by Access Company and is indexed and abstracted in the SRM Database of Social Research Methodology.