Filtering and identification of stochastic volatility for parabolic type factor models

被引：0
|
作者：
Aihara, ShinIchi
Bagchi, Arunabha
机构：
[1] Tokyo Univ Sci, Dept Mech & Syst Design, Nagano 3910292, Japan
[2] Univ Twente, Dept Appl Math, NL-7500 AE Enschede, Netherlands
[3] Univ Twente, FELab, NL-7500 AE Enschede, Netherlands
来源：
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2006年 / 2卷 / 05期
关键词：
factor model; stochastic volatility; nonlinear filtering; MLE;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We consider the dynamics of forward rate process which is modelled by a parabolic type infinite-dimensional factor model with stochastic volatility. The parameters included in the stochastic volatility dynamics are estimated from the factor process as the observation data. Based on the maximum likelihood technique, we propose the off-line identification scheme and provide some numerical examples.
引用
收藏
页码：917 / 925
页数：9
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