Abdou Kâ Diongue () (UFR SAT - Université Gaston Berger - Université Gaston Berger de Saint-Louis, School of Economics and Finance - Queensland University of Technology) Dominique Guegan () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, Ecole d'économie de Paris - Paris School of Economics - Université Panthéon-Sorbonne - Paris I)
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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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Length: Date of creation: Jan 2008 Date of revision: Handle: RePEc:hal:papers:halshs-00235179_v1
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