基于羊群效应的投资者跟随行为研究
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摘要
现有羊群行为理论将跟随者观察到其他投资者行为作为投资的前提假设,已经成功解释了诸多复杂金融现象。但是,已有理论并没有对影响跟随者跟随策略的因素进行深入的探讨,也缺少在微观方面对对跟随者行为特点的研究。本文的目的就是在对经典羊群行为理论梳理的基础上,找到影响我国证券市场投资者跟随行为的影响因素,并研究这些具体因素是如何影响跟随者的行为。
本文通过分析我国证券市场的环境特色,将投资者在证券市场上观察到的由其他投资者投资行为所反映出未来股票价格信息看作是一个随机过程。通过建立跟随者的效用函数,利用动态最优化理论构建了羊群跟随者决策模型,分析了不同因素对投资者跟随行为的影响。在考虑其他跟随者的影响基础上将模型进行了扩展,并与初始模型结论进行比较,探讨了存在其他跟随者时对研究目标最优跟随策略的影响。最后,将行为金融学中时间偏好不一致的假设引入到最优跟随策略的模型中,讨论具有该特点的跟随者的行为模式。通过上述三个模型得到了六个有待检验的结论。
根据本文第三章模型Ⅰ、模型Ⅱ的结论,投资者的跟随行为会受到必要报酬率、股票波动率等因素的影响,为我们研究我国机构投资者的羊群效应提供了切入口。运用所建模型对机构投资者的跟随行为进行经验研究。首先对机构投资者的特点进行分析；其次回顾了机构投资者的非理性行为,结合中外研究结果,分析研究我国机构投资者的独特之处；然后利用面板数据的分析方法,考察股票收益率因素、上市公司财务因素以及公司股权结构等不同因素对整体机构投资者当期的持股数量和持股比例的影响；最后考察了不同类型投资者的投资行为。
在当前中国股票市场上已上市流通的股票,一般情况下均有涨跌幅的限制,每天股票价格只能在前一交易日收盘价格的上下10%内进行浮动。这种制度设计的目的是防止股票在一日之内剧烈波动,使得引起股票价格上涨的信息能够有足够的时间披露给市场,起到了稳定股票市场的作用。但事物总有正反两个方面：涨跌幅的限制会引起股票的价格在当日没有充分反映股票的内在价值。根据第三章模型Ⅲ的结论,当股票价格上涨至一定程度后,其他投资人会由于决策时间变短而变得更不理智,引起跟随者提前投资。很多有资金实力的投资者会利用市场的这种机制,通过操纵股票价格使其在短期内获得不菲的收益。但这种操纵出现的频率往往在整体股票市场比较活跃的阶段比较高,因为整体证券市场活跃会使得更多的跟随者跟随,因此在整体证券市场活跃的阶段,每一交易日涨停的股票较多。
为了研究该现象背后的形成机制以及对股票价格的影响,本文在模型Ⅲ的基础上,针对股票涨跌停的制度进行了专门研究。考虑在股票涨停的事件下,对其他投资者由于不能按照常规的效用进行决策,所引起投资者非理性行为的影响进行实证分析,并利用马尔可夫模型对中国证券市场状态进行科学区分,根据分析的结果选择研究涨停事件的时间段；在分类的基础上利用多元统计分析,重点考察在股票涨停情况下,各种投资者的投资行为,并分析这种投资行为能否为投资者带来长期的超额收益。
通过上述研究,找到了影响投资跟随者投资决策的各种因素,并且对机构投资者投资行为的实证检验也验证了模型的有效性,同时还对我国涨停事件的形成机制提出了相关的政策建议。
综上,本文的创新点体现在以下三个方面：
一、应用行为金融理论,构筑了不同状态下羊群行为跟随者的跟随时机选择模型,研究影响其行为的因素；
二、应用跟随时机选择模型,对影响机构投资者跟随行为的主要因素分别构建了相应的测量模型并进行验证；
三、针对股票涨停事件中的中小投资者跟随行为,应用跟随时机选择模型构建了相应的测量模型,并对股票价格的影响进行分析。
In this paper, we expand the classic herd behavior theory. Though analyzing the Chinese specific stock market environment, we treat the stock price, which inferred from the first investor's behavior, as a stochastic process. Using the dynamic theory, we find when one of the herd do invest and analyze the impact factors. After that, we expand our model to include all herds to follow. We compare the outcome of new model to the previous finding. Finally, we take the time-inconsistency preference into consideration, which would occur when the stock price suddenly rise into the upper price limit, and draw interesting findings. Above all, we have six conclusions, which will be empirically tested.
According to the Model I and ModelⅡ's conclusion, stock market average returns, stock volatility and other factors would impact herd behavior. This provides us the entry point to study the herding of institutional investor. We successfully test the model's conclusion. First, we analyze the characteristics of institutional investors; Second we review of the irrational behavior of institutional investors; then we use the panel data analyze various factors, how which would impact the overall institutional investors herding behavior. Finally, we examine and compare the investment behavior of different types of investor:funds, brokerage, brokerage financial products, QFII, insurance companies, pension funds, annuity, trust companies, finance companies, banks, general corporate, non-financial listed companies.
According to the ModelⅢ's conclusion, when the stock price rapidly rises to the upper limit, the investor may be surfer the time-inconsistency preference problem, which would strongly trigger herding behavior. So there are someone would utilize this mechanism to get profit. We use high-frequency data to study whether stock rise to the upper limit is manipulated or not. Firstly, we utilizes Markov switching model to study Chinese stock market volatility. Based on Shanghai Composite Index's historical data, we estimate the parameters of Markov switching model and get the figure of the whole sample smooth probability. WE uses this nonlinear method to accurately classify the different period by the volatility. Based the classified period, utilizing the high frequency stock data, we statistically analyze various factors impact the second day's stock price return after the stock up to the limit broad. We empirically verify the stock price's different behaviors respectively caused by new information or price manipulation. According to our conclusion, we propose advises to improve Chinese Stock Price Limit System.
本文通过分析我国证券市场的环境特色,将投资者在证券市场上观察到的由其他投资者投资行为所反映出未来股票价格信息看作是一个随机过程。通过建立跟随者的效用函数,利用动态最优化理论构建了羊群跟随者决策模型,分析了不同因素对投资者跟随行为的影响。在考虑其他跟随者的影响基础上将模型进行了扩展,并与初始模型结论进行比较,探讨了存在其他跟随者时对研究目标最优跟随策略的影响。最后,将行为金融学中时间偏好不一致的假设引入到最优跟随策略的模型中,讨论具有该特点的跟随者的行为模式。通过上述三个模型得到了六个有待检验的结论。
根据本文第三章模型Ⅰ、模型Ⅱ的结论,投资者的跟随行为会受到必要报酬率、股票波动率等因素的影响,为我们研究我国机构投资者的羊群效应提供了切入口。运用所建模型对机构投资者的跟随行为进行经验研究。首先对机构投资者的特点进行分析；其次回顾了机构投资者的非理性行为,结合中外研究结果,分析研究我国机构投资者的独特之处；然后利用面板数据的分析方法,考察股票收益率因素、上市公司财务因素以及公司股权结构等不同因素对整体机构投资者当期的持股数量和持股比例的影响；最后考察了不同类型投资者的投资行为。
在当前中国股票市场上已上市流通的股票,一般情况下均有涨跌幅的限制,每天股票价格只能在前一交易日收盘价格的上下10%内进行浮动。这种制度设计的目的是防止股票在一日之内剧烈波动,使得引起股票价格上涨的信息能够有足够的时间披露给市场,起到了稳定股票市场的作用。但事物总有正反两个方面：涨跌幅的限制会引起股票的价格在当日没有充分反映股票的内在价值。根据第三章模型Ⅲ的结论,当股票价格上涨至一定程度后,其他投资人会由于决策时间变短而变得更不理智,引起跟随者提前投资。很多有资金实力的投资者会利用市场的这种机制,通过操纵股票价格使其在短期内获得不菲的收益。但这种操纵出现的频率往往在整体股票市场比较活跃的阶段比较高,因为整体证券市场活跃会使得更多的跟随者跟随,因此在整体证券市场活跃的阶段,每一交易日涨停的股票较多。
为了研究该现象背后的形成机制以及对股票价格的影响,本文在模型Ⅲ的基础上,针对股票涨跌停的制度进行了专门研究。考虑在股票涨停的事件下,对其他投资者由于不能按照常规的效用进行决策,所引起投资者非理性行为的影响进行实证分析,并利用马尔可夫模型对中国证券市场状态进行科学区分,根据分析的结果选择研究涨停事件的时间段；在分类的基础上利用多元统计分析,重点考察在股票涨停情况下,各种投资者的投资行为,并分析这种投资行为能否为投资者带来长期的超额收益。
通过上述研究,找到了影响投资跟随者投资决策的各种因素,并且对机构投资者投资行为的实证检验也验证了模型的有效性,同时还对我国涨停事件的形成机制提出了相关的政策建议。
综上,本文的创新点体现在以下三个方面：
一、应用行为金融理论,构筑了不同状态下羊群行为跟随者的跟随时机选择模型,研究影响其行为的因素；
二、应用跟随时机选择模型,对影响机构投资者跟随行为的主要因素分别构建了相应的测量模型并进行验证；
三、针对股票涨停事件中的中小投资者跟随行为,应用跟随时机选择模型构建了相应的测量模型,并对股票价格的影响进行分析。
In this paper, we expand the classic herd behavior theory. Though analyzing the Chinese specific stock market environment, we treat the stock price, which inferred from the first investor's behavior, as a stochastic process. Using the dynamic theory, we find when one of the herd do invest and analyze the impact factors. After that, we expand our model to include all herds to follow. We compare the outcome of new model to the previous finding. Finally, we take the time-inconsistency preference into consideration, which would occur when the stock price suddenly rise into the upper price limit, and draw interesting findings. Above all, we have six conclusions, which will be empirically tested.
According to the Model I and ModelⅡ's conclusion, stock market average returns, stock volatility and other factors would impact herd behavior. This provides us the entry point to study the herding of institutional investor. We successfully test the model's conclusion. First, we analyze the characteristics of institutional investors; Second we review of the irrational behavior of institutional investors; then we use the panel data analyze various factors, how which would impact the overall institutional investors herding behavior. Finally, we examine and compare the investment behavior of different types of investor:funds, brokerage, brokerage financial products, QFII, insurance companies, pension funds, annuity, trust companies, finance companies, banks, general corporate, non-financial listed companies.
According to the ModelⅢ's conclusion, when the stock price rapidly rises to the upper limit, the investor may be surfer the time-inconsistency preference problem, which would strongly trigger herding behavior. So there are someone would utilize this mechanism to get profit. We use high-frequency data to study whether stock rise to the upper limit is manipulated or not. Firstly, we utilizes Markov switching model to study Chinese stock market volatility. Based on Shanghai Composite Index's historical data, we estimate the parameters of Markov switching model and get the figure of the whole sample smooth probability. WE uses this nonlinear method to accurately classify the different period by the volatility. Based the classified period, utilizing the high frequency stock data, we statistically analyze various factors impact the second day's stock price return after the stock up to the limit broad. We empirically verify the stock price's different behaviors respectively caused by new information or price manipulation. According to our conclusion, we propose advises to improve Chinese Stock Price Limit System.
引文
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