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

被引：17
|
作者：
Liu, Shuangzhe [1 ]
Heyde, Chris C. [2 ,3 ]
机构：
[1] Univ Canberra, Sch Informat Sci & Engn, Canberra, ACT 2601, Australia
[2] Columbia Univ, Dept Stat, New York, NY USA
[3] Australian Natl Univ, Inst Math Sci, Canberra, ACT 0200, Australia
来源：
STATISTICAL PAPERS | 2008年 / 49卷 / 03期
关键词：
heteroskedasticity; likelihood; BHHH method; Newton-Raphson method;
D O I：
10.1007/s00362-006-0026-3
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
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.
引用
收藏
页码：455 / 469
页数：15
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