Filtering of a Multi-Dimension Stochastic Volatility Model

被引：1
|
作者：
Luo, Shangzhen [1 ]
机构：
[1] Univ No Iowa, Dept Math, Cedar Falls, IA 50614 USA
来源：
STOCHASTIC ANALYSIS AND APPLICATIONS | 2011年 / 29卷 / 03期
关键词：
EM algorithm; Filtering; Hidden Markov model; Stochastic volatility; PARAMETER-ESTIMATION; INTEREST-RATES; EM ALGORITHM; REGIME; OPTIONS; TIME;
D O I：
10.1080/07362994.2011.548986
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this article, we study a stochastic volatility model for a class of risky assets. We assume that the volatilities of the assets are driven by a common state of economy, which is unobservable and represented by a hidden Markov chain. Under this hidden Markov model (HMM), we develop recursively computable filtering equations for certain functionals of the chain. Expectation maximization (EM) parameter estimation is then used. Applications to an optimal asset allocation problem with mean-variance utility are given.
引用
收藏
页码：407 / 423
页数：17
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