极端条件下中国股票市场信息交易概率研究

发布时间：2018-02-21 06:39

本文关键词： 微观市场结构 VPIN 突发事件高频交易　出处：《天津大学》2014年硕士论文　论文类型：学位论文

【摘要】：近年来金融市场风起云涌,突发事件和极端情况层出不穷,这给金融市场的稳定带来了极大威胁。与此同时,市场微观结构理论发展十分迅速,这为从微观的角度来研究极端条件下交易者行为提供了可能性。从某种程度上来讲,可以说信息是决定交易者行为的主要因素,投资者根据掌握的信息进行投资和交易,掌握信息的准确性与完整性对投资所取得的效果有着深刻影响。然而信息的88-不对称性导致市场交易双方的利益失衡,论文以此为基础,对我国股票市场信息交易进行了动态刻画,研究了股票信息交易概率在市场突发条件下的动态变化过程。本文的研究分为以下四个部分,具体研究内容与所得结论如下:首先,以光大“乌龙指”事件为研究主体,探讨了信息交易概率与股票价格之间的关系,发现信息交易概率的增大伴随着股票的剧烈波动,虽然VPIN模型不能对此类非信息事件的发生做出预测,但是能够对股票价格趋于平缓进行提前判断。其次,根据中国股票市场的交易数据,探讨了VPIN度量值的影响因素,并分别讨论了这些因素对VPIN度量的稳健性的影响。结果表明,在现有条件下对VPIN的估算具有一定的稳健性。再次,研究了VPIN与未来股票价格波动之间的关系,研究表明,在特定的参数下VPIN值与未来股票价格的波动表现出较为明显的正相关性,这意味着,VPIN值越高,流动风险越大,未来股票价格的不可预测性越高。最后,以一般的股票涨停事件为研究对象,研究了股票涨停前以及涨停期间信息交易概率的统计特征。研究结果表明,在股票发生涨停前,信息交易概率会在个别交易日或者连续几个交易日内呈现出异常升高的现象,而在涨停期间,VPIN值同样处于很高的水平,这一研究结果进一步证实了VPIN对未来股票价格的异常波动会起到有效的预警作用。本文突破性的将VPIN这一模型应用于中国股票市场的微观结构研究之中,发现在极端条件下VPIN与股票价格之间存在着密切关系,有效利用此模型能够促进投资者的理性行为,同时也为监管者提供了一种有效的风险管理手段。
[Abstract]:In recent years, the financial market is surging, sudden events and extreme situations emerge in endlessly, which has brought great threat to the stability of the financial market. At the same time, the theory of market microstructure has developed very rapidly. This provides the possibility to study the behavior of traders in extreme conditions from a micro perspective. To some extent, information is the main determinant of traders' behavior, and investors invest and trade according to the information they have at their disposal. Mastering the accuracy and completeness of information has a profound impact on the effect of investment. However, the 88-asymmetry of information leads to the imbalance of the interests of both sides of the market. In this paper, the dynamic characteristics of information trading in Chinese stock market are described, and the dynamic process of information trading probability under sudden market conditions is studied. The research in this paper is divided into the following four parts. The specific research contents and conclusions are as follows: first, Based on the "Oolong finger" event of Everbright University, this paper discusses the relationship between the information trading probability and the stock price, and finds that the increase of the information transaction probability is accompanied by the sharp fluctuation of the stock. Although the VPIN model can not predict the occurrence of this kind of non-information event, it can judge the stock price in advance. Secondly, according to the trading data of Chinese stock market, the influencing factors of VPIN measure are discussed. The effects of these factors on the robustness of VPIN metric are discussed respectively. The results show that the estimation of VPIN is robust under existing conditions. Thirdly, the relationship between VPIN and stock price volatility in the future is studied. Under certain parameters, the VPIN value is positively correlated with the future stock price fluctuation, which means that the higher the VPIN value, the greater the liquidity risk and the higher the unpredictability of the future stock price. The statistical characteristics of the information trading probability before and during the stock trading limit are studied with the general stock fluctuation event as the research object. The results show that before the stock price limit occurs, the statistical characteristics of the information trading probability during the stock trading limit are studied. The probability of information trading will show an abnormal rise in individual trading days or several consecutive trading days, and the VPIN value will also be at a very high level during the trading limit. The results of this study further confirm that VPIN will play an effective and early warning role in the future abnormal volatility of stock prices. This paper applies the VPIN model to the study of the microstructure of Chinese stock market. It is found that there is a close relationship between VPIN and stock price under extreme conditions. The effective use of this model can promote the rational behavior of investors and provide an effective risk management method for regulators.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.51

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