摘要
我国的金融时间序列存在普遍的波动性现象,而波动性又存在尖峰厚尾现象。首先对反映波动性特征的厚尾金融随机波动模型(SV-T)进行贝叶斯分析,然后构造基于Gibbs抽样的MCMC数值计算过程进行仿真分析,最后利用DIC准则对SV-N模型和SV-T模型进行优劣比较。研究结果表明:在模拟我国股市的波动性的方面,SV-T模型比SV-N模型更优,更能反应我国股市的尖峰后尾的特性,并且证明了我国股市具有很强的波动持续性。
Our country＇s finance time series exist the umversal piaenomenon ot volatility, anO tiae volatility has me property or Peak and heavy-tail. The first is to analyze Bayesian heavy-tail finance stochastic volatility model reflecting the volatility characteristic. The second is to design a Markov chain Monte Carlo algorithm procedure with Gibbs sampler to carry on simulation analysis. At last the SV-N model and SV-T model in the quality were compared using the DIC criterion. The findings indicate that, in simulating the volatility of stock market of China, the SV-T model is superior to the SV-N model, which can characterize the leptokurtic of stock returns in stock market of China. It is proved that the stock market in china has a high persistence of volatility.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2008年第9期2479-2482,共4页
Journal of System Simulation
基金
国家自然科学基金项目(7070138)
教育部新世纪优秀人才支持计划项目(NCET050704)
教育部人文社科规划项目(06JA910001)
