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The Measurement And Application Of Liquidity In China 's A - Share Market

Posted on:2014-05-18Degree:MasterType:Thesis
Country:ChinaCandidate:Y T ZhuFull Text:PDF
GTID:2279330434972870Subject:Financial project management
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This article takes the inspiration from Cetin et.al.(2006), in which we use a the proxy of liquidity in Chinese stocks. The larger the a, the more illiquid a stock is. The proxy a was formed by stochastic supply curve of individual stock and calculated by using "tick" trading data. My estimation of the a shows its stochastic behavior, but this diminishes when considering combination of average intra-day stock prices, as was already proved in Cetin et.al.(2006).Based on the calculated a, three main applications construct the rest of the article.First application compares the a proxy with other popular liquidity proxies and use Monte Carlo simulation to estimate liquidity costs bearing in individual stocks. In this part I found that different proxies of liquidity in Chinese Stock Market behave approximately similar. However, there do exists difference when comparing qualitative and quantitative proxies. Taking all A shares as a whole, I found that stocks in Shanghai Stock Exchange are more liquid than that in Shenzhen Stock Exchange. Moreover, VaR simulation gives the positive and somehow concave relationship between liquidity risk proportions (in total risk) and trading volumes. In our example, when trading volume increases to10000lots,50%of total risk is liquidity risk in individual stock.Second application considers the influences of other factors on the a, in which market micro-structure factors such as trading volume proves to be effective in predicting cross-sectional a, and in which through fundamentals only market value can positively affect a. EPS announcement do not statistically affect the a, whilst the a can somehow be different in various industries.Third application tends to construct the liquidity-adjusted asset pricing model by excluding liquidity risk as part of the idiosyncratic risk first, and after confirming this using Chinese Stock Market data, the model is formed with careful examination. However, the robustness of the model remains to be test, and whether the Chinese Stock Market has the’Illiquidity Premium’remains to be tested.
Keywords/Search Tags:Liquidity, α-Value, Comparison, VaR, Influential Factors, Asset Pricing
PDF Full Text Request
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