RANK TEST OF UNIT-ROOT HYPOTHESIS WITH AR-GARCH ERRORS

GUILI LIAO; QIMENG LIU; RONGMAO ZHANGSHIFANG ZHANG

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RANK TEST OF UNIT-ROOT HYPOTHESIS WITH AR-GARCH ERRORS

机译：RANK TEST OF UNIT-ROOT HYPOTHESIS WITH AR-GARCH ERRORS

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摘要

A robust rank test based on the regression rank score process is proposed to test the unit-root hypothesis under linear GARCH noises in this article. It is shown that the limit distribution of the rank test is a function of a stable process and a Brownian motion. The finite sample studies indicate that the proposed test statistic exhibits a reliable size and a remarkable power under a variety of tail index α, and performs better than other unit-root tests based on least square procedure, such as the augmented Dick Fuller (ADF) and the Phillips-Perron (PP) tests.

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来源
《Journal of time series analysis》 |2022年第5期|695-719|共25页
作者
GUILI LIAO; QIMENG LIU; RONGMAO ZHANGSHIFANG ZHANG;
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作者单位

School of Mathematics and Statistics, Fujian Normal University, Fuzhou, China;

School of Data Science, Zhejiang University of Finance and Economics, Hangzhou, China;

School of Mathematical Sciences, Zhejiang University, Hangzhou, China;

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正文语种英语
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关键词
Unit-root; GARCH; heavy tail; α-stable process and rank score;

RANK TEST OF UNIT-ROOT HYPOTHESIS WITH AR-GARCH ERRORS

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