A new estimator for LARCH processes
Résumé
The aim of this paper is to provide a new estimator of parameters for LARCH(∞) processes, and thus also for LARCH(p) or GLARCH(p,q) processes. This estimator results from minimising a contrast leading to a least squares estimator for the absolute values of the process. Strong consistency and asymptotic normality are shown, and convergence occurs at the rate √n as well in short or long memory cases. Numerical experiments confirm the theoretical results and show that this new estimator significantly outperforms the smoothed quasi-maximum likelihood estimators or weighted least squares estimators commonly used for such processes.
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