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Research On The Impact Of Stock Splitting Ratio On Investor's Micro-trading Characteristics

Posted on:2019-12-14Degree:MasterType:Thesis
Country:ChinaCandidate:D LiFull Text:PDF
GTID:2439330623962733Subject:Finance
Abstract/Summary:PDF Full Text Request
This paper intends to examine the impact of stock splitting on the trading characteristics of investors from the perspective of market microstructure.Specifically,this paper examines the market response to stock split and the changes of investors' behavior in the market microstructure,including signal hypothesis,liquidity hypothesis,transaction scope hypothesis,optimal unit of price change hypothesis etc,and whether they are valid in China's securities market.In order to achieve the above goal,this paper studies from two aspects.On the one hand,with the help of the more mature information probability model,market trading orders are divided into market price orders and limit price orders according to certain criteria.At the same time,the maximum likelihood estimation of the information probability model of trading day is established,the changes of each variable are estimated by the model.By estimating the models of two groups of data,high-split ratio and low-split ratio,it is found that the background and purpose of high-split ratio and low-split ratio may not be the same.Low-proportion companies tend to have better performance,and genuinely lower stock prices,changing the capital structure of the demand,rather than through speculation in stock splitting events to cater to stakeholders.On the other hand,in order to test the applicability of information probability model in China,this paper measures the market reaction,liquidity and the change of optimal price after stock splitting by directly calculating the price difference,accumulated price difference,market depth,accumulated market depth and relative minimum price change before and after stock splitting.It shows that the estimation results of the information probability model are roughly consistent with the measured results.
Keywords/Search Tags:Stock split, Information probability model, Investor behavior, Split ratio
PDF Full Text Request
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