A new estimator for LARCH processes
提出一种针对LARCH过程参数的新估计量，通过最小化对比函数得到绝对值的最小二乘估计，证明强相合性和渐近正态性，数值实验显示优于常用估计量。
The aim of this article is to provide a new estimator of parameters for LARCH processes, and thus also for LARCH or GLARCH processes. This estimator results from minimizing 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 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.