信息及其扩散对证券市场的影响
本文关键词:信息及其扩散对证券市场的影响 出处:《天津大学》2014年博士论文 论文类型:学位论文
更多相关文章: 证券市场信息 Ward权熵指标 连续渗流 厚尾现象 Lévy过程
【摘要】:信息在证券市场中具有举足轻重的作用。信息的内容及价值影响市场中投资者的决策;信息的扩散导致市场波动等,都是证券市场的研究热点。本文基于证券市场中静态和动态两类信息,使用不同的信息处理技术,分别从两个角度讨论了信息对投资者的效用和信息扩散对市场波动产生的影响。首先,针对静态信息,主要是上市公司的财务数据,从财务聚类的角度进行研究。由于对股票聚类方法的研究较多,但对聚类结果的优劣、取舍却较难评定,本文提出了一个评价聚类结果优劣的Ward权熵指标,以帮助投资者对股票进行聚类和筛选。该指标兼具股票聚类所要求的准确性和面向投资者的实用性特点,从基于距离度量的偏差损失最小和基于信息熵度量的信息量损失最小两个角度衡量聚类结果的优劣。Ward权熵指标适用于不同的聚类方法、相似性度量、以及指标加权等状态,具有广泛的适应性。文中验证了在聚合聚类下,指标关于聚类数K单调不降。通过实证,分析了指标的特性,并使用该指标对不同聚类方法和聚类结果进行了较为有效的评价。其次,针对动态信息,本文讨论了证券市场信息扩散的羊群效应及其对市场波动的影响。借鉴与信息扩散结构相似的连续渗流理论,本文详细讨论了利用连续渗流模拟价格或指标波动的模型构造、理论分析和实证。主要介绍了渗流及连续渗流的理论和应用背景。给出一个基本的RCM波动模型,进而重点讨论单串和多串的连续渗流模型及其改进,使所构造的模型不断贴近市场的真实状态。在不同的模型下均验证出波动率收敛于L′evy过程,而非有效市场假说条件下得到的Wiener过程。通过程序实现,形象地展示了在连续渗流模型下,信息扩散的机制及上、下临界状态的差异,并通过模拟波动过程,验证了收益率的厚尾现象。最后根据不同参数的变化导致收益率变化的状态,解释了参数的作用。
[Abstract]:Information plays an important role in the securities market. The diffusion of information leads to the fluctuation of the market, which is the research hotspot of the securities market. Based on the static and dynamic information in the securities market, different information processing techniques are used in this paper. This paper discusses the effect of information on investors and the influence of information diffusion on market volatility from two angles. Firstly, aiming at static information, it mainly focuses on the financial data of listed companies. From the perspective of financial clustering, because of the more research on the stock clustering method, but the advantages and disadvantages of the clustering results, it is difficult to evaluate. In this paper, a Ward weight entropy index is proposed to evaluate the clustering results. In order to help investors to cluster and screen the stock. This index has both the accuracy required by stock clustering and the practicability of investor oriented. From the two aspects of minimum deviation loss based on distance measurement and minimum information loss based on information entropy measure, Ward weight entropy index is suitable for different clustering methods, similarity measurement. In this paper, it is verified that the cluster number K of the index is not monotone decreasing under the aggregation clustering. Through the empirical analysis, the characteristics of the index are analyzed. This index is used to evaluate the different clustering methods and clustering results. Secondly, the dynamic information is analyzed. In this paper, the herding effect of information diffusion in securities market and its influence on market fluctuation are discussed, and the continuous seepage theory similar to information diffusion structure is used for reference. This paper discusses in detail the construction of a model for simulating price or index fluctuation by continuous seepage. This paper mainly introduces the theory and application background of seepage flow and continuous seepage, gives a basic RCM wave model, and then discusses the continuous seepage model with single string and multiple strings and its improvement. The constructed model is kept close to the real state of the market and the volatility converges to the Levy process under different models. The Wiener process obtained under the condition of the non-efficient market hypothesis is realized by the program, which vividly shows the mechanism of information diffusion and the difference of the upper and lower critical states under the continuous seepage model. By simulating the fluctuation process, the thick tail phenomenon of the return rate is verified. Finally, the effect of the parameter is explained according to the state of the change of the return rate caused by the change of the different parameters.
【学位授予单位】:天津大学
【学位级别】:博士
【学位授予年份】:2014
【分类号】:F832.51
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