证券市场资产价格的动力学关联性研究

发布时间：2018-02-13 15:22

本文关键词： 复杂网络非线性互信息无标度特性波动聚集 HHT方法收益和波动溢出效应　出处：《南京信息工程大学》2012年硕士论文　论文类型：学位论文

【摘要】：金融市场是一个大尺度的动力学复杂系统,资产价格的波动性一直是金融动力学研究的一个重要课题,传统的研究方法是通过建立多元统计的模型对有限股票之间的波动关联性进行研究,然而,市场上每两只股票之间都互相关联,基于此,本文引入复杂网络理论通过分析股票网络来全面揭示股票之间的波动关联性。波动溢出效应也是证券市场波动性研究当中的一个重要方向,本文引入经验模态分解的方法通过沪深股市波动的相位关系动态分析沪深市场之间的溢出效应。本文的主要工作和创新成果如下： (1)以上海市场2001年1月2日至2010年12月7日中的501只股票作为研究样本,根据股票价格波动非线性关联的长度确定了观测窗口的时间长度,然后采用互信息法和滑动窗口的方法构建了2000个动态股票关联网络。 (2)分析了2000个动态股票关联网络的平均度、平均簇系数、幂指数、拟合误差和拟合优度p值随时间的变化情况,研究结果发现2005年7月1日,2007年10月16日和2008年12月1日左右的这三段时期的股票关联网络不具有无标度特性,且这三段时期是上海市场的转折时期。 (3)分析了大盘指数波动聚集程度与股票网络拓扑结构变化之间的关系,实证发现在证券市场的转折时期股票网络不具备无标度特性,各股票价格波动之间的相互依赖性变弱,大盘指数呈随机波动行为；相反,在证券市场正常发展时期股票网络具有无标度特性,大盘指数的波动聚集度较高。所以在一定意义上股票网络的无标度特性是股票市场正常发展的标志。 (4)以上证指数和深证综合指数1991年12月30日至2007年10月8日的收盘价为研究样本,利用EMD方法获取了沪深两个市场日收盘价的收益和波动的趋势成分,然后通过希尔伯特变换获得各成分的瞬时相位和瞬时幅度。根据沪深两市收益与波动趋势成分相位关系的时变特征,揭示了沪深股市的动态溢出效应,且发现2001年是中国股市的转折之年。本文的分析方法和研究结论将有助于我国证券市场上的投资者做出正确的投资选择,减少损失,保持我国国民经济长期稳定健康的发展。
[Abstract]:Financial market is a large-scale dynamic complex system, the volatility of asset prices has been an important subject in the research of financial dynamics. The traditional research method is to study the volatility correlation between limited stocks by establishing a multivariate statistical model. However, every two stocks in the market are interrelated, based on this, In this paper, the complex network theory is introduced to comprehensively reveal the volatility correlation between stocks by analyzing the stock network. Volatility spillover effect is also an important direction in the research of volatility in the securities market. In this paper, the empirical mode decomposition method is introduced to dynamically analyze the spillover effects between Shanghai and Shenzhen stock markets through the phase relationship of the volatility in Shanghai and Shenzhen stock markets. The main work and innovative results of this paper are as follows:. Using 501 stocks in Shanghai market from January 2nd 2001 to December 7th 2010 as the research sample, the time length of the observation window is determined according to the length of nonlinear correlation of stock price fluctuations. Then 2000 dynamic stock correlation networks are constructed by mutual information method and sliding window method. (2) the variation of average degree, average cluster coefficient, power exponent, fitting error and goodness of fit p over time of 2000 dynamic stock correlation networks are analyzed. The results show that the stock correlation networks of July 1st 2005, October 16th 2007 and December 1st 2008 do not have scale-free characteristics, and these three periods are the turning points of the Shanghai market. This paper analyzes the relationship between the aggregation degree of large market index volatility and the change of the topological structure of stock network. It is found that the stock network does not have scale-free characteristics in the transition period of the stock market, and the interdependence among the stock price fluctuations becomes weaker. On the contrary, in the normal development of the stock market, the stock network has scale-free characteristics. Therefore, the scale-free characteristic of the stock network is the symbol of the normal development of the stock market in a certain sense. Taking the closing price of Shanghai Stock Exchange Index and Shenzhen Stock Exchange Composite Index from December 30th 1991 to October 8th 2007 as the research sample, using EMD method to obtain the earnings and trend components of the daily closing price of Shanghai and Shenzhen markets. Then the instantaneous phase and instantaneous amplitude of each component are obtained by Hilbert transform. According to the time-varying characteristics of the relationship between returns and the phase of fluctuating trend components, the dynamic spillover effect of Shanghai and Shenzhen stock markets is revealed. And find 2001 is the turning point year of Chinese stock market. The analytical methods and conclusions of this paper will be helpful for investors in China's securities market to make correct investment choices, reduce losses, and maintain the long-term, stable and healthy development of China's national economy.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F224;F832.51

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