M-ESTIMATION IN GARCH MODELS
推导了广义自回归条件异方差（GARCH）模型中一类M估计量的渐近正态性，涵盖最小绝对偏差、Huber估计和拟极大似然估计，仅需误差分布存在分数阶无条件矩等温和条件。
This paper derives asymptotic normality of a class of M -estimators in the generalized autoregressive conditional heteroskedastic (GARCH) model. The class of estimators includes least absolute deviation and Huber's estimator in addition to the well-known quasi maximum likelihood estimator. For some estimators, the asymptotic normality results are obtained only under the existence of fractional unconditional moment assumption on the error distribution and some mild smoothness and moment assumptions on the score function.