Estimation of k-factor GIGARCH process : a Monte Carlo study.

In this paper, we discuss the parameter estimation for a k-factor generalized long memory process with conditionally heteroskedastic noise. Two estimation methods are proposed. The first method is based on the conditional distribution of the process and the second is obtained as an extension of Whittle's estimation approach. For comparison purposes, Monte Carlo simulations are used to evaluate the finite sample performance of these estimation techniques.

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Year of publication:	2008-01
Authors:	Diongue, Abdou Kâ ; Guegan, Dominique
Institutions:	Centre d'Économie de la Sorbonne, Université Paris 1 (Panthéon-Sorbonne)
Subject:	Long memory \| Gegenbauer polynomial \| heteroskedasticity \| conditional sum of squares \| Whittle estimation

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Extent:	application/pdf
Series:	Documents de travail du Centre d'Economie de la Sorbonne. - ISSN 1955-611X.
Type of publication:	Book / Working Paper
Language:	English
Notes:	18 pages
Classification:	C53 - Forecasting and Other Model Applications
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005510593