Tail behaviours of multiple-regime threshold AR models with heavy-tailed innovations

IF 0.7 4区经济学 Q3 ECONOMICS

Studies in Nonlinear Dynamics and Econometrics Pub Date : 2022-06-27 DOI:10.1515/snde-2020-0071

Jiazhu Pan, Yali He

引用次数: 0

Abstract

Abstract This paper studies the tail behaviours of the stationary distribution of multiple-regime threshold AR models with multiple heavy-tailed innovations. It is shown that the marginal tail probability has the same order as that of the innovation with the heaviest tail. Other new results in this paper include the geometric ergodicity and the tail dependence of TAR models with multiple heavy-tailed innovations.

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具有重尾创新的多域阈值AR模型的尾部行为

摘要本文研究了具有多重重尾创新的多状态阈值AR模型平稳分布的尾部行为。结果表明，边际尾部概率与尾部最重的创新具有相同的阶数。本文中的其他新结果包括具有多重重尾创新的TAR模型的几何遍历性和尾部依赖性。

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

Studies in Nonlinear Dynamics and Econometrics Multiple-

CiteScore

1.40

自引率

12.50%

发文量

期刊介绍： Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.