Research On The Stock Market Liquidity Of The Trading Volume Duration

With the advent of the era of big data, the theory about technology ofcomputer to store huge amounts of date,related date statistics and data miningdiscovery is constantly evolving. This type of technology and methods will alsobe bound to use in the stock market data. Traditional analysis of stock marketdata are based on the time axis units，they use GARCH，SV and other modelsaiming at finding volatility and clustering features of time series such as tradingvolume and the price. An important feature of these models is the samplingintervals, when unequal intervals, using such model to analyze likely to causedistortion in the conclusions.In the stock market, data constituts by all types of transaction which we callultra-high rfequency data. An important feature of such data is the random arrivaltime of the transaction, the arrival time intervals ranging. Such data generallyincludes several variables such time interval, the transaction and price,Anyanalytical method which discard time interval is not reasonable to someextent，also the traditional model is clearly not applicable to this type of UHF data,so the time variable should be take into account when make model for suchvariables UHF data. In addition，one of the main functions of the stock market isto enable investors to quickly and efficiently execute the transaction under thecircumstances of transaction costs as low as possible.In other words, the marketmust provide suiffcient liquidity.In this context，This article put for word point about using period of thetrading volume to depict intraday liquidity from the perspective of the timeperiod and according to change of the trading volume, the use of indicators tomeasure the time when the given the amount of trading can be implementedcompletely-Not only to. measure the overall liquidity of the overall transactionvolume through the period, but also take advantage of transaction period of theinitiative sale or purchase to measure the amount of unilateral market liquidity.Since the transaction period changes dynamicly with time and has a certainagglomeration, therefore it can also be predicted.This paper ifrstly reviews the research status about related areas、mobilityconcepts，then introduce econometric model analysis framework for the period ina larger space,covering the processing and analysis of data the linear andnonlinear ACD model (with WACD (11) model, for example).This paper selects12stocks of Shanghai and Shenzhen as a sample, and Comparative analysis theduration of trading volume of three dimensions such as entirety, initiative to buyand initiative to sell，with the purpose to characterize their mobility features. Onthe basis of the duration of trading volume,at the same time, introducting the Variable of price changes,atfer adjustment for varying time intervals of data, Thispaper uses UHF-GARCH model to analyze the price distribution under theconditions of the duration. Finally, we have come to an important conclusion thatWACD (1,1) and UHF-GARCH model can be applied to analyze liquidity ofChina’s securities market...