A GARCH (1,1) estimator with (almost) no moment conditions on the error term

A least squares estimation approach for the estimation of a GARCH (1,1) modelis developed. The asymptotic properties of the estimator are studied given mild regularity conditions, which require only that the error term has a conditionalmomen t of some order. We establish the consistency, asymptotic normality and the law of iterated logarithm for our estimate. The finite sample properties are assessed by means of an extensive simulation study.

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Year of publication:	2006-08
Authors:	PREMINGER, Arie ; STORTI, Giuseppe
Institutions:	Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain
Subject:	GARCH (1 \| 1) \| least squares estimation \| consistency \| asymptotic normality \| law of the iterated logarithm

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Extent:	application/pdf
Series:	CORE Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series UNIVERSITE CATHOLIQUE DE LOUVAIN, Center for Operations Research and Econometrics (CORE) Number 2006068
Classification:	C13 - Estimation ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005008182