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

被引：12
|
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
收藏
页码：27 / 51
页数：25
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