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Jean-Michel Zakoian, CRES Print
Friday, 02 April 2010, 14:30 - 15:30

Optimal predictions of powers of conditionally heteroskedastic processes

Jean-Michel Zakoian, Centre de Recherche en Economie et Statistique, Paris

Abstract: In conditionally heteroskedastic models, the optimal prediction of powers, or logarithms, of the absolute process has a simple expression in terms of the volatility process and an expectation involving the independent process. A standard procedure for estimating this prediction is to estimate the volatility by gaussian quasi-maximum likelihood (QML) in a first step, and to use empirical means based on rescaled innovations to estimate the expectation in a second step. This paper establishes the asymptotic properties of this procedure, as well as those of an alternative one-step procedure, based on an appropriate non-gaussian QML estimation of the model. The performances of the two approaches are compared via asymptotic results and using simulations. An empirical application based on stock returns is proposed.

Location: Plaine 2NO906
Contact: Jacqueline Bottemanne