沪深两市股指时间序列突变点贝叶斯检测模型研究

The Research on Bayesian Measure Model of Change Points in Shanghai and Shenzhen Stock Index Time Series

股指时间序列突变点的检测是股指波动规律研究领域中的一个重要问题。依据贝叶斯原理提出的突变点检测分析模型,用Matlab工具软件对该模型进行了仿真,并且在实证分析中应用该模型分别对上证综合指数和深证成份指数月度时间序列数据进行了突变点检测分析,准确地确定了两市的突变点,和相应的后验概率分布,并解释了突变点形成的经济和政策背景。

The measurement of change points in stock index time series is an important issue in the stock index volatility research area. Based on the Bayesian theory, the paper puts forward a measurement model of change points and uses Matlab to imitate the model. By applying the model to Shanghai and Shenzhen Stock Index time series, the paper gets the change point precisely as well as the posterior probability distribution. This hdps to explain the background of economic and policy for the change points.