基于随机波动性模型的中国股票市场波动性估计

摘要

The Markov Chain Monte Carlo (MCMC)'s simulation of Bayesian Analysis method has conducted scientific analysis and study against the volatility of China's stock market. Based on dynamic stochastic volatility model, this kind of de⁃sign can make more accurate prediction on parameter setting and the choice of volatility sequences. Through Experi⁃ment on Chinese stock actual data, and by comparing the ARCH class models, the article fully analyses the link be⁃tween volatility and heteroscedasticity of the stock market.%马尔科夫链蒙特卡洛(MCMC)模拟的贝叶斯分析法针对我国股票市场的波动性进行了科学的分析与研究，这种基于动态随机性的波动模型的设计，能够在参数设定和波动性序列的选择上进行较精准的预测。通过对我国股票实际数据进行实验，并通过比较ARCH类模型，文章充分解析股票市场波动性与异方差之间的关联。