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随机波动模型参数估计的新算法及其在上海股市的实证 被引量：8

A New Algorithm for Estimating Stochastic Volatility Model and the Application in Shanghai Stock Market
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摘要 研究用马尔科夫链蒙特卡罗(MCMC)算法估计随机波动模型的参数问题.基于“前向滤波,后向抽样”方法提出一种新算法,并将新算法同原有算法进行了比较.然后利用新算法对上海股市进行波动性分析,发现中国涨跌停板制度对波动的持续性估计有着重要的影响,忽视这些因素将会导致波动的持续性被高估. In this paper, A new markov chain monte carlo algorithm for estimating stochastic volatility model is given. And the new algorithm is compared with old algorithms. Then authors apply stochastic volatility model to analyze the volatility of Shanghai stock market by the new algorithm. Empirical results indicate that stochastic volatility model performs well. On the other hand empirical results also indicate that price limit have much effect on the persistence of volatility.
作者 刘凤芹 吴喜之
机构地区 北京师范大学社会发展与公共政策研究所 中国人民大学统计学院
出处 《系统工程理论与实践》 EI CSCD 北大核心 2006年第4期27-31,共5页 Systems Engineering-Theory & Practice
关键词 随机波动模型 马尔科夫链蒙特卡罗(MCMC) 波动 stochastic volatility model Markov chain Monte Carlo volatility
分类号 O212 [理学—概率论与数理统计] F830 [经济管理—金融学]
  • 相关文献

参考文献9

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共引文献43

同被引文献71

  • 1余素红,张世英,宋军.基于GARCH模型和SV模型的VaR比较[J].管理科学学报,2004,7(5):61-66. 被引量：76
  • 2孟利锋,张世英,何信.SV模型参数估计的经验特征函数方法[J].系统工程,2004,22(12):92-95. 被引量：9
  • 3周宏山,冀云.非对称随机波动模型在中国股市的应用[J].统计与信息论坛,2007,22(4):70-73. 被引量：4
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引证文献8

二级引证文献40

系统工程理论与实践
2006年 第4期

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