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隔夜信息对中国股市影响研究

—— 基于不对称SV模型
A Research on Impacts of Overnight Information on Chinese Stock Market

作者: 专业:经济系统分析与管理 导师:梁艳 年度:2010 学位:硕士  院校: 大连理工大学

Keywords

overnight information, asymmetric SV model, leverage effect, noise

        信息的披露和扩散是股票市场波动的内在动因,然而这种信息有很多都是在非交易时间段积累的,这里我们称之为隔夜信息。在当前全球经济一体化的背景下,世界各国的资本市场紧密相连,对全球宏观经济信息甚至是一些微观经济信息都会作出相同的反映。另外因为时差原因,欧美股市与香港股市和内地股市非同步交易,欧美股市的交易信息也在我国股市非交易时间段积累。因而对隔夜信息的挖掘,并通过数学工具量化,研究其对我国股票市场的预测能力,这对我国股票市场的深入理解具有深远意义。本文基于有效市场假说理论(EMH),结合证券市场微观结构理论,对隔夜信息对我国股票市场波动和预期收益影响展开理论分析和实证研究。论文先运用一个基于隔夜信息对称的SV模型,分析隔夜信息对我国股票市场的影响大小。考虑到不同类别信息冲击对股市波动的存在不对称效应,然后构建一个基于隔夜信息的不对称SV模型,分析不同类别的隔夜信息对我国股票市场的影响。最后基于行为金融学的理论,投资者在不同的市场行情下对信息会有着不同的反映,运用加入隔夜信息的不对称SV模型对上涨周期的股市和下跌周期的股市分别进行研究。最后,通过实证研究分析,表明隔夜信息对我国股市具有预测能力,经对比分析,得出隔夜信息对香港股市有着更大的预测能力;这主要是由于内地股市信息披露程度不高,噪声交易比较多,另外内地股市开放程度不够高也是很重要的原因。信息冲击对内地股市和香港股市的波动均表现出“杠杆效应”,但下跌行情中,这种不对称性尤为明显;致使这一现象产生主要原因是我国资本市场缺乏有效的做空机制,尤其是内地股市,另外这与投资者在下跌行情中容易对利空消息过度反映过度是密不可分的。
    The proliferation and disclosure of information is the inherent motivation of the stock market, however lots of the information is accumulated in the inactive time, and here we call them the overnight information. Especially in the current context of global economic integration, the world capital markets are closely related, then they will make a consistent response to the global macro-economic information and even some micro-economic information. Therefore mining the overnight information and being quantified by mathematical tools to study the predictive ability of the Chinese stock market, there will be a far-reaching significance to get a deep understanding of our stock market.Based on the Efficient Market Hypothesis(EMH) and combined with the microstructure theory of securities market, we make a theoretical analysis and empirical research to evaluate the effects of the overnight information on the stock market volatility and expected returns. Firstly, we apply a symmetric SV model which is based on the overnight information to analyze impacts of the overnight information on our stock markets. Secondly, the different types of overnight information will arise different impact, we take the asymmetric effects of the stock market into account, and then build an asymmetric SV model based on the overnight information to analysis the different types of overnight information on the Chinese stock market. Finally, based on the behavioral finance theory, investors will make different reaction to the same news under different market conditions, thus we apply the asymmetric SV model based on the overnight information to study the up cycle and down cycle.The empirical analysis shows that the overnight information has predictive ability on the Chinese stock market, through comparative analysis we find that the overnight information has a greater predictive power in the Hong Kong stock market. This is mainly because the transparency of information disclosure is not high, there is too much noise trading, and the mainland stock market is not open enough. Impact of information on the mainland and Hong Kong stock market volatility shows a "leverage effect". We find that there will be a greater asymmetry when the stock market is on the down cycle, especially in the mainland stock market, which is due to the lack of effective short mechanism, and it is related to the fact that investors will make overreaction to the bad news when the stock market is on the down cycle.
        

隔夜信息对中国股市影响研究

摘要4-5
Abstract5
1 绪论8-14
    1.1 研究背景与意义8-9
    1.2 相关文献综述9-11
        1.2.1 国外研究现状9-10
        1.2.2 国内研究现状10-11
    1.3 研究内容和创新11-14
        1.3.1 研究的思路及内容11-13
        1.3.2 主要创新点13-14
2 信息对股票市场影响的理论分析14-23
    2.1 信息冲击影响与股票价格波动的理论解释14-18
        2.1.1 有效市场理论14-16
        2.1.2 混合分布假说理论16-17
        2.1.3 股票市场信息"杠杆效应"说17-18
    2.2 投资者对股票信息的不同反应18-21
        2.2.1 投资者对信息的反应过度19-20
        2.2.2 投资者对信息的反应不足20-21
    2.3 隔夜信息界定与度量21-23
        2.3.1 隔夜信息概念的界定21
        2.3.2 隔夜信息的度量21-23
3. 隔夜信息对股市影响的不对称SV模型构建23-34
    3.1 SV模型与GARCH模型的比较23-30
        3.1.1 GARCH类模型24-25
        3.1.2 SV族模型25-26
        3.1.3 SV模型的优势26-30
    3.2 基本模型构建30-34
        3.2.1 隔夜信息对股市影响的SV模型31-32
        3.2.2 基于隔夜信息的不对称SV模型32-34
4 隔夜信息对中国股市影响的实证分析34-48
    4.1 样本数据的选取34
    4.2 隔夜信息统计特征34-37
    4.3 基于SV模型的隔夜信息对中国股市影响37-44
        4.3.1 应用修正的SV模型37-39
        4.3.2 加入隔夜信息的SV模型39-42
        4.3.3 不同的SV族模型优劣的DIC比较42-43
        4.3.4 实证小结43-44
    4.4 基于不对称SV模型的隔夜信息对中国股市影响44-48
        4.4.1 上涨行情中的隔夜信息影响44-46
        4.4.2 下跌行情中的隔夜信息影响46-48
5 结论与政策建议48-50
    5.1 结论48-49
    5.2 政策建议49
    5.3 研究不足及展望49-50
参考文献50-53
附录A 附录内容名称53-56
攻读硕士学位期间发表学术论文情况56-58
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