A new estimator for LARCH processes

IF 1.2 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Journal of Time Series Analysis Pub Date : 2023-03-27 DOI:10.1111/jtsa.12689

Jean-Marc Bardet

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引用次数: 1

Abstract

The aim of this article is to provide a new estimator of parameters for LARCH $(\infty)$ processes, and thus also for LARCH $(p)$ or GLARCH $(p, q)$ processes. This estimator results from minimizing a contrast leading to a least squares estimator for the absolute values of the process. Strong consistency and asymptotic normality are shown, and convergence occurs at the rate $\sqrt{n}$ as well in short or long memory cases. Numerical experiments confirm the theoretical results and show that this new estimator significantly outperforms the smoothed quasi-maximum likelihood estimators or weighted least squares estimators commonly used for such processes.

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一种新的LARCH过程估计方法

本文的目的是为LARCH $(\infty)$过程提供一种新的参数估计，从而也为LARCH $(p)$或GLARCH $(p,q)$过程提供一种新的参数估计。这个估计量是通过最小化导致过程绝对值的最小二乘估计量的对比度得到的。强一致性和渐近正态性表明，收敛发生在速率$\sqrt n$以及短或长记忆的情况下。数值实验证实了理论结果，并表明该估计量明显优于光滑拟极大似然估计量或加权最小二乘估计量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Time Series Analysis 数学-数学跨学科应用

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.