基于股市领先滞后效应的股票关联分析

发布时间：2018-10-16 18:55

【摘要】：股市的变幻莫测在给投资者带来巨额收益的同时,也使投资者面临巨大的风险,分析预测股票价格的未来走势,无论是对广大投资者还是宏观经济管理部门,都有着十分重要的意义。本文基于股市中个股间的领先滞后效应,结合灰色系统理论方法,对股票进行关联分析。从股票量价关系入手,深入探究股票之间的时滞动态影响,进而对股票走势实行短期预测。这将对投资者如何较好地把握股票买卖时机,进行投资决策起到重要的指导作用。主要内容如下：第一章主要对已有的相关研究结论进行归纳总结,从股市领先滞后效应、股票间关联分析以及灰色模型在股市中的应用三方面进行了阐述。第二章从有效市场假说及市场摩擦理论两方面说明现实股票市场是一个存在信息收集成本和噪音交易行为的摩擦市场,股票对信息反应速度的快慢差异是形成个股间领先滞后效应的主要原因。并探讨了我国股市信息反应模式的特点及明显的“羊群效应”,指出“羊群效应”会使得股价不可避免地出现反应过度或反应不足,初步证实了我国股市中存在领先滞后效应的推断。第三章以股票的交易价格作为研究对象,从价格关系入手探究股票间存在的时滞动态影响。为了建立符合股市数据特点的模型,本文提出了基于函数信息的灰色关联度计算方法来对股票进行关联分析。将股票每日的价格波动图像看作一个函数,当函数信息未知时,提出采用分段二次插值方法对原函数曲线进行逼近,并给出了不同函数间的差异性度量公式。基于领先滞后效应中存在的时滞期,引入时滞变量,建立时滞灰关联模型,通过对银行板块相关股票进行实证分析,说明了模型的可行性及有效性。第四章对股票的量价关系进行了探讨,阐述了金融市场量价关系的四类理论模型及相关研究方法,说明股票的成交量对于股票的波动性具有不可被忽略的解释能力。为了同时考虑两个数据行为特征对股票间关联度的影响,引入矩阵灰关联度模型,提出基于函数信息的矩阵时滞灰关联分析,将研究对象从一维拓展到二维。通过与采用单纯地基于股票交易价格的时滞灰关联分析方法得到的结果进行对比,发现基于量价关系的时滞灰关联分析方法与实际情况更为一致,更具有合理性,能够为投资者提供更有价值的参考信息。第五章介绍了本文的主要研究内容、研究成果和创新点,并对未来的研究工作进行了展望。
[Abstract]:Are of great significance. Based on the leading lag effect between individual stocks in the stock market, this paper combines the grey system theory to analyze the stock association. Starting with the relationship between stock volume and price, this paper probes into the dynamic influence of delay between stocks, and then carries out short-term prediction of stock trend. This will play an important guiding role for investors how to grasp the timing of stock trading and make investment decisions. The main contents are as follows: the first chapter summarizes the existing research conclusions from three aspects: the leading lag effect of stock market, the correlation analysis between stocks and the application of grey model in stock market. The second chapter shows that the real stock market is a frictional market with information collection cost and noise trading behavior from two aspects: efficient market hypothesis and market friction theory. The difference of the speed of stock reaction to information is the main reason of leading lag effect between stocks. The conclusion that there is a leading lag effect in China's stock market is preliminarily confirmed. In order to establish a model that accords with the characteristics of stock market data, this paper presents a grey relational degree calculation method based on function information to analyze the correlation of stock. The daily price fluctuation image of stock is regarded as a function. When the information of the function is unknown, the piecewise quadratic interpolation method is proposed to approximate the original function curve, and the measurement formula of the difference between different functions is given. The fourth chapter discusses the relationship between volume and price of stock, expounds four kinds of theoretical models and related research methods of the relationship between volume and price in financial market, and explains that stock trading volume has an explanatory power that can not be ignored for the volatility of stock. By comparing with the results obtained by using the grey correlation analysis method based on stock trading price, it is found that the time-delay grey correlation analysis method based on the relationship between quantity and price is more consistent with the actual situation and more reasonable. To provide investors with more valuable reference information.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F830.91;F224

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