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Title: Estimation for heavy tailed moving average process (English)
Author: Ouadjed, Hakim
Author: Mami, Tawfiq Fawzi
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 54
Issue: 2
Year: 2018
Pages: 351-362
Summary lang: English
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Category: math
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Summary: In this paper, we propose two estimators for a heavy tailed MA(1) process. The first is a semi parametric estimator designed for MA(1) driven by positive-value stable variables innovations. We study its asymptotic normality and finite sample performance. We compare the behavior of this estimator in which we use the Hill estimator for the extreme index and the estimator in which we use the t-Hill in order to examine its robustness. The second estimator is for MA(1) driven by stable variables innovations using the relationship between the extremal index and the moving average parameter. We analyze their performance through a simulation study. (English)
Keyword: extreme value theory
Keyword: mixing processes
Keyword: tail index estimation
MSC: 60G70
MSC: 62G32
idZBL: Zbl 06890425
idMR: MR3807720
DOI: 10.14736/kyb-2018-2-0351
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Date available: 2018-05-30T16:11:00Z
Last updated: 2020-01-05
Stable URL: http://hdl.handle.net/10338.dmlcz/147199
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