On estimation in conditional heteroskedastic time series models under non-normal distributions

被引：0
|
作者：
Shuangzhe Liu
Chris C. Heyde
机构：
[1] University of Canberra,School of Information Sciences and Engineering
[2] Columbia University,Department of Statistics
[3] Australian National University,Mathematical Sciences Institute
来源：
Statistical Papers | 2008年 / 49卷
关键词：
Heteroskedasticity; Likelihood; BHHH method; Newton-Raphson method;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Financial time series data are typically observed to have heavy tails and time-varying volatility. Conditional heteroskedastic models to describe this behaviour have received considerable attention. In the present paper, our purpose is to examine some of these models in a general setting under some non-normal distributions. A likelihood based approach to estimation is used. New comparisons of estimators and their efficiencies are discussed.
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