中国股票市场跳跃行为的实证分析

发布时间：2018-03-17 02:07

本文选题：跳-扩散模型　切入点：均值、方差跳跃点　出处：《北方工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：跳跃现象在经济、金融、工业流程控制等领域普遍存在,对跳跃的把握程度直接影响到是否能够避免不必要的损失以及能否驾驭该领域里有益的转变时机。在金融资产价格序列中,研究人员是通过对资产价格的建模来研究这种跳跃特性的。在对股指收益率建模中,跳-扩散模型对收益率序列的拟合效果非常好,能很好地反应收益率序列的一些特征。本文提出了一个新的跳跃点检测算法,并将之运用到中国股票市场的实证分析中。跳跃点可分为均值跳跃点和方差跳跃点,针对其不同特性,我们选取V统计量检测均值跳跃点,并构造了一个新统计量用来检测方差跳跃点。本文主要工作如下：首先,利用方差跳跃点前后收益率序列偏差变化显著这个特性,本文构造了一个新的方差跳跃检验统计量--类偏差比(DLR)统计量,并给出了基于非对称Poisson跳-扩散模型阈值确定的模拟方法。其次,本文根据新的方差跳跃检验统计量DLR和均值跳跃检验统计量V提出了一种新的跳跃点检测算法。最后,本文将新算法应用到中国股票市场的实证分析中。我们选取了中国股票市场中五个主要的股指数据(上证指数,上证50指数,深证综合指数,深证成份股指数,沪深300指数),以2007年1月4日到2011年12月30日五年的股指日收盘价作为样本数据,利用本文提出的新方法对中国股票市场进行了实证分析。实证分析表明中国股票市场对于政府政策的依赖性较大,且受国际股市波动的影响较大；另外,我们还需要不断地加强政府政策的监管力度,建立健全的法律规章制度体系,确保外部环境正常和谐地运行,推进中国股票市场的创新性改革,加强和完善股票市场组织管理机构,从而使得中国股票市场更加成熟、稳定。
[Abstract]:The phenomenon of jumping is widespread in the fields of economy, finance, industrial process control, etc. The degree of mastery of the jump has a direct bearing on whether unnecessary losses can be avoided and whether the beneficial timing of the transition in this area can be harnessed. In the modeling of stock index yield, the jump-diffusion model fits the yield series very well and can well reflect some characteristics of the return series. In this paper, a new jumping point detection algorithm is proposed and applied to the empirical analysis of Chinese stock market. The jump point can be divided into mean jump point and variance jump point. We select V statistic to detect mean jump point and construct a new statistic to detect variance jump point. The main work of this paper is as follows: firstly, a new variance jump test statistic, class deviation ratio (DLR), is constructed by using the characteristic of significant variation of return sequence deviation before and after variance jump point. A simulation method based on the threshold of asymmetric Poisson hop-diffusion model is given. Secondly, according to the new variance jump test statistic DLR and the mean jump test statistic V, a new jumping point detection algorithm is proposed. This paper applies the new algorithm to the empirical analysis of Chinese stock market. We have selected five main stock index data in Chinese stock market (Shanghai Stock Exchange Index, Shanghai Stock Exchange 50 Index, Shenzhen Stock Exchange Composite Index, Shenzhen Stock Exchange component Index. The Shanghai-Shenzhen 300 index is based on the daily closing price of the stock index for five years from January 4th 2007 to December 30th 2011. The new method proposed in this paper is used to analyze the Chinese stock market. The empirical analysis shows that the Chinese stock market depends heavily on the government policy and is greatly affected by the volatility of the international stock market. We also need to constantly strengthen the supervision of government policies, establish a sound legal and regulatory system, ensure the normal and harmonious operation of the external environment, and promote the innovative reform of China's stock market. Strengthen and perfect the organization and management of stock market, thus make Chinese stock market more mature and stable.
【学位授予单位】：北方工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.51;F224

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