Asymptotics for semi-strong augmented GARCH(1,1) model

Oesook Lee; Jooyoung Kim

doi:10.1080/03610926.2021.1887894

Asymptotics for semi-strong augmented GARCH(1,1) model

Oesook Lee, Jooyoung Kim

Department of Statistics

Research output: Contribution to journal › Article › peer-review

Abstract

In this article, we study a family of so-called semi-strong augmented GARCH(1,1) model where the innovation process is strictly stationary and mixing instead of independent and identically distributed. We give a necessary and sufficient condition for stationarity of the process and study the functional central limit theorems for (Formula presented.) and u_t when the process is stationary. We also investigate the dynamic behavior of semi-strong GARCH(1,1) model when it is non stationary.

Original language	English
Pages (from-to)	8093-8109
Number of pages	17
Journal	Communications in Statistics - Theory and Methods
Volume	51
Issue number	23
DOIs	https://doi.org/10.1080/03610926.2021.1887894
State	Published - 2022

Bibliographical note

Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.

Keywords

-mixing
L -NED
Semi-strong augmented GARCH(1,1) model
functional central limit theorem
α-mixing

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10.1080/03610926.2021.1887894

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Asymptotics for semi-strong augmented GARCH(1,1) model

Abstract

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Keywords

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