ROBUST RECURSIVE ESTIMATION OF GARCH MODELS

被引：4
|
作者：
Cipra, Tomas [1 ]
Hendrych, Radek [1 ]
机构：
[1] Charles Univ Prague, Fac Math & Phys, Dept Probabil & Math Stat, Sokolovska 83, Prague 18675 8, Czech Republic
来源：
KYBERNETIKA | 2018年 / 54卷 / 06期
关键词：
GARCH model; Kalman filter; outlier; robust recursive estimation; volatility; FORECASTING VOLATILITY; LIKELIHOOD ESTIMATORS; KALMAN FILTER; TIME-SERIES; OUTLIERS; ARCH; INFERENCE;
D O I：
10.14736/kyb-2018-6-1138
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The robust recursive algorithm for the parameter estimation and the volatility prediction in GARCH models is suggested. It seems to be useful for various financial time series, in particular for (high-frequency) log returns contaminated by additive outliers. The proposed procedure can be effective in the risk control and regulation when the prediction of volatility is the main concern since it is capable to distinguish and correct outlaid bursts of volatility. This conclusion is demonstrated by simulations and real data examples presented in the paper.
引用
收藏
页码：1138 / 1155
页数：18
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