Asymptotically optimal tests for non-linear autoregressive model with β-ARCH errors

被引：0

作者：

Laib, Naamane ^{[1
]}

Lounis, Tewfik ^{[1
]}

机构：

[1] CY Cergy Paris Univ, Lab AGM, UMR 8088, CNRS, F-95000 Cergy, France

来源：

STATISTICS & PROBABILITY LETTERS | 2021年 / 178卷

关键词：

Contiguity; Efficiency; LAN; Quadratic mean differentiability; Time series models; beta-ARCH models;

D O I：

10.1016/j.spl.2021.109184

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 develops optimal statistical tests for testing certain class of non-linear time series models contiguous to a non-linear autoregressive processes with beta-ARCH errors. The statistical tests are based on the Local Asymptotic Normality-LAN-(established via the quadratic mean differentiability) of the log-likelihood ratio of the studied Model when its parameters are estimated. Their local power are also computed. Some examples related to financial models are considered. Our approach uses mainly an efficient estimators of Bouzebda and Lounis (2019). (C) 2021 Published by Elsevier B.V.

引用

页数：10

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