Quasi-maximum likelihood estimation in GARCH processes when some coefficients are equal to zero

Christian Francq and Jean-Michel Zakoian

Stochastic Processes and their Applications, 2007, vol. 117, issue 9, 1265-1284

Abstract: The asymptotic distribution of the quasi-maximum likelihood (QML) estimator is established for generalized autoregressive conditional heteroskedastic (GARCH) processes, when the true parameter may have zero coefficients. This asymptotic distribution is the projection of a normal vector distribution onto a convex cone. The results are derived under mild conditions. For an important subclass of models, no moment condition is imposed on the GARCH process. The main practical implication of these results concerns the estimation of overidentified GARCH models.

Keywords: Boundary; of; the; parameter; space; Conditional; heteroskedasticity; GARCH; model; Quasi-maximum; likelihood; estimation; Non-normal; asymptotic; distribution (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (43)

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