基于交易量持续期的股市流动性研究

发布时间：2018-03-20 23:05

本文选题：WACD模型　切入点：超高频数据　出处：《上海师范大学》2014年硕士论文　论文类型：学位论文

【摘要】：伴随着大数据时代的到来，计算机存储海量数据的技术及相关的数据统计和数据挖掘发现理论不断发展，这类技术方法也将必然会用到股票市场的数据中。传统分析股票市场数据都是以单位时间为轴，，运用GARCH、SV等模型对这类数据进行建模，旨在发现时间序列上的交易量、价格等波动性和集聚性等特征。这类模型的一个重要特点是等间隔取样，当间隔不等时，运用该类模型分析容易造成结论的失真。在股市中，由各类逐笔交易构成的数据我们称之为超高频数据。该类数据的一个重要特点是交易时随机到达的，即到达的时间间隔不等，这类数据一般有时间间隔、交易及价格等几个变量。任何摈弃时间间隔的分析方法都有一定得不合理性，此前传统的模型显然不太适用这类超高频数据，因此需要考虑到时间变量对此类超高频数据建模。另外，证券市场的一个主要功能就是在交易成本尽可能低的情况下，使投资者能够迅速、有效地执行交易。换句话说,也就是市场必须提供足够的流动性。本文正是在这样的背景下，从时间的角度根据交易量的变化提出了使用交易量期间来刻画日内流动性的观点，利用这一指标来衡量执行完给定交易量所耗费的时间。不仅通过整体交易量期间来度量整体的流动性，而且同时也利用主动性卖出或买入交易量期间分别来度量单边的市场流动性。由于交易量期间是随着时间而动态变化的，并且具有一定得集聚性，因此其也是可以被预测的。本文首先回顾了国内外相关领域的研宄现状和流动性的概念及度量方法,随后就使用了较大篇幅来介绍针对期间的计量模型分析框架，涵盖了线形和非线性ACD模型（以WACD(1，1)模型为例），期间数据的处理和分析过程。本文选取了上海、深圳（主板/中小板/创业板）的12只股票为样本，从整体和主动性买单以及主动卖单构成的交易量持续期三个维度进行对比分析，刻画其流动性特点。在交易量持续期基础上，同时引进价格变化，针对不等时间间隔的数据进行调整后，运用UHF-GARCH模型分析持续期条件下的价格分布特点^发现WACD(1，1)和UHF-GARCH模型能够较好的分析我国证券市场的流动性。
[Abstract]:With the advent of big data's era, the technology of computer storage of massive data and the related data statistics and data mining discovery theory are constantly developing. The traditional analysis of stock market data is based on the unit time axis and models such as GARCHN SV are used to model the data in order to find the trading volume in time series. One of the important characteristics of this kind of model is the equi-interval sampling. When the interval is not equal, it is easy to use this model to analyze the distortion of the conclusion. In the stock market, data consisting of all kinds of individual trades is called UHF data. One of the important features of these data is the random arrival at the time of trading, that is, the time interval of arrival varies, and such data usually have time intervals. Some variables, such as trading and price. Any analytical method that abandons the time interval has some irrationality. The traditional model is obviously not suitable for this kind of UHF data. One of the main functions of the securities market is to enable investors to execute transactions quickly and efficiently at the lowest possible transaction cost. In other words, That is, the market must provide sufficient liquidity. In this context, this paper puts forward the viewpoint of using trading volume period to depict intraday liquidity from the perspective of time, according to the change of trading volume. This indicator is used to measure the time taken to execute a given transaction volume. At the same time, the active selling or buying trading volume is used to measure the unilateral market liquidity, which can be predicted because the trading volume period changes dynamically with time and has a certain degree of agglomeration. This paper first reviews the current research situation and the concept and measurement methods of liquidity in related fields at home and abroad, and then introduces the econometric model analysis framework for the period. This paper covers the linear and nonlinear ACD model (taking WACD-1) model as an example, and the process of data processing and analysis. 12 stocks in Shanghai and Shenzhen (main board / small and medium-sized board / gem) are selected as samples. This paper makes a comparative analysis from the three dimensions of transaction duration, which consists of total and active payment and active selling order, to characterize its liquidity characteristics. On the basis of the duration of trading volume, the price changes are introduced at the same time. After adjusting the data of different time intervals, it is found that the UHF-GARCH model and the UHF-GARCH model can better analyze the liquidity of China's securities market by using the UHF-GARCH model to analyze the price distribution characteristics under the condition of duration.
【学位授予单位】：上海师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F832.51

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