Estimation of k-Factor Gigarch Process: A Monte Carlo Study

Diongue Abdou Ka (1) , Dominique Guegan (2, 3)

1 UGB - Université Gaston Berger de Saint-Louis Sénégal
2 CES - Centre d'économie de la Sorbonne
3 PSE - Paris School of Economics

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, using four different conditional distribution functions.

Mots clés: Long memory; Gegenbauer polynomial; heteroskedasticity; Conditional Sum of Squares; Whittle estimation

Domaines: Economies et finances; Statistiques [math.ST]; Théorie [stat.TH]; Modélisation et simulation

Diongue Abdou Ka, Dominique Guegan. Estimation of k-Factor Gigarch Process: A Monte Carlo Study. Communications in Statistics - Simulation and Computation, 2008, 37 (10), pp.2037-2049. ⟨10.1080/03610910802304994⟩. ⟨halshs-00375758⟩