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| 中国股市量价关系分析中的后验分布构造与模拟 | |
| 引用本文： | 王彩凤,孙晓霞,郑珊.中国股市量价关系分析中的后验分布构造与模拟[J].数学的实践与认识,2012,42(12):37-47. |
| 作者姓名： | 王彩凤 孙晓霞 郑珊 |
| 作者单位： | 1. 北京科技大学自动化学院,北京100083;北京科技大学 数理学院.北京100083 2. 中国科学院数学与系统科学研究院应用数学所,北京,100190 3. 神州数码信息系统有限公司,北京,100085 |
| 摘 要： | 研究中国股票市场中的两个重要指标:股票价格与交易量,随机波动模型具有长期波动性预测能力,只是由于参数估计的困难而没有受到重视.随着马尔可夫链蒙特卡罗(MCMC)方法和计算机计算能力的提高,这种困难是可以克服的.采用基于马尔可夫链蒙特卡罗(MCMC)模拟技术的贝叶斯估计方法,在基于引入预期交易量和非预期交易量的随机波动模型下,对模型参数进行后验分布的构造,并以2005年1月-2012年5月的上证综合指数的每日收盘指数及相应的日成交量序列为样本,通过实证仿真得到参数结果值.结果表明,非预期交易量对股市价格的影响要大于预期交易量. |
| 关 键 词： | 价格波动 交易量 随机波动模型 MCMC MDH假说 |
Posteriori construction and simulation on Return Volatility and Trading Volume of China Stock Market |
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| WANG Cai-feng , SUN Xiao-xia , ZHENG Shan.Posteriori construction and simulation on Return Volatility and Trading Volume of China Stock Market[J].Mathematics in Practice and Theory,2012,42(12):37-47. | |
| Authors: | WANG Cai-feng SUN Xiao-xia ZHENG Shan |
| Institution: | 1.School of Automation,University of Science and Technology Beijing,Beijing 100083,China) (2.School of Mathematics and Physics,University of Science and Technology Beijing,Beijing 100083,China) (3.Institute of Applied Mathematics,Academy of Mathematics and System Science,Chinese Academy of Science,Beijing 100190,China) (4.Digital China Holdings Limited,Beijing 100085,China) |
| Abstract: | The stock price and trading volume are the two importaht indicators in China stock market.Stochastic Volatility(SV)model can play its role in persistence prediction of the stock market,but it is not emphasized for its difficulties in estimating the model parameters. With the development of Markov Chain Monte Carlo(MCMC)methods and computer science, it is possible to overcome them. Based on Bayesian estimation method,this paper constructs the posterior distribution in MCMC methods.Secondly,by doing the empirical simulation for the sample data from January,2005 to April,2012 in China stock market,the paper estimates the parameters' value in the SV model.The results indicate that non-expected volume plays greater role in China stock market than expected volume. |
| Keywords: | return volatility trading volume SV model MCMC MDH hypothesis |
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