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.
|Date of creation:||Jan 2008|
|Publication status:||Published in Documents de travail du Centre d'Economie de la Sorbonne 2008.04 - ISSN : 1955-611X. 2008|
|Note:||View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00235179|
|Contact details of provider:|| Web page: https://hal.archives-ouvertes.fr/|
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