Finite sample properties of maximum likelihood and quasi-maximum likelihood estimators of egarch models
用蒙特卡洛方法研究EGARCH(1,1)模型的最大似然和拟最大似然估计量在有限样本下的表现，发现最大似然估计量表现合理，而高斯拟最大似然估计量在数据存在条件超额峰度时表现很差。
In this paper I examine finite sample properties of the maximum likelihood and quasi-maximum likelihood estimators of EGARCH(1,1) processes using Monte Carlo methods. I use response surface methodology to summarize the results of a wide array of experiments which suggest that the maximum likelihood estimator has reasonable finite sample properties. The Gaussian quasi-maximum likelihood estimator has poor finite sample properties when the data generating process has conditional excess kurtosis. Some of these poor properties appear to be asymptotic in nature.