  The aim of this paper is to provide a new estimator of parameters for
LARCH$(\infty)$ 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 $\sqrt
n$ 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.
