Goodness-of-fit tests for Log-GARCH and EGARCH models

被引：11

作者：

Francq, Christian ^{[1
,2
]}

Wintenberger, Olivier ^{[3
,4
]}

Zakoian, Jean-Michel ^{[5
,6
]}

机构：

[1] CREST, BP 60149, F-59653 Villeneuve Dascq, France

[2] Univ Lille, BP 60149, F-59653 Villeneuve Dascq, France

[3] Univ Paris 06, LSTA, 4 Pl Jussieu, F-75005 Paris, France

[4] Univ Copenhagen, LSTA, 4 Pl Jussieu, F-75005 Paris, France

[5] CREST, 15 Blvd Gabriel Peri, F-92245 Malakoff, France

[6] Univ Lille, 15 Blvd Gabriel Peri, F-92245 Malakoff, France

来源：

TEST | 2018年 / 27卷 / 01期

关键词：

EGARCH; LM tests; Invertibility of time series models; Log-GARCH; Portmanteau tests; Quasi-maximum likelihood; TIME-SERIES MODELS;

D O I：

10.1007/s11749-016-0506-2

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper studies goodness-of-fit tests and specification tests for an extension of the Log-GARCH model, which is both asymmetric and stable by scaling. A Lagrange-multiplier test is derived for testing the extended Log-GARCH against more general formulations taking the form of combinations of Log-GARCH and exponential GARCH (EGARCH). The null assumption of an EGARCH is also tested. Portmanteau goodness-of-fit tests are developed for the extended Log-GARCH. An application to real financial data is proposed.

引用

页码：27 / 51

页数：25

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