摘要
金融数据的波动性一直是经济学研究的热点问题之一,随机波动率模型(SV)在波动率建模中有着重要的应用.马尔科夫链蒙特卡罗(MCMC)方法是估计参数的一种有效方法,给出估计一类二元SV模型参数的MCMC算法,并通过WinBUGS软件编程实现了该算法.文章最后给出了模型和程序的一个实际应用.
The volatility of financial data is one of the hot spots in the economics study. Stochastic Volatility （SV） model has important applications in the modeling of volatility. The Markov Chain Monte Carlo （MCMC） method is an important method in the estimation of parameters. In this paper, a MCMC algorithm for estimates a class of binary SV model parameters was given out, and the algorithm was realized by programming through the software of WinBUGS. Finally, the article gives the models and procedures of a practical application.
出处
《合肥学院学报（自然科学版）》
2010年第1期27-29,共3页
Journal of Hefei University :Natural Sciences
关键词
多元随机波动率模型
MCMC方法
后验分布
GIBBS抽样
multivariate stochastic volatility model
Markov Chain Monte Carlo method
posterior distribution
Gibbs sample
