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Research On Volatility's Characters Of Chinese Security Market From Perspective Of Microstructrue

Posted on:2009-08-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:D PengFull Text:PDF
GTID:1119360242490785Subject:Management Science and Engineering
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It is an important research field in finance to analyze systematically and deeply on the features of stock market volatilities in theory and practice. As a new market, Chinese Stock Market is unstable, high complex, unexpected, and its price fluctuates greatly and violently, compared with mature capital market overseas. Therefore, it is significant in theory and practice to analyze volatilities of Chinese Stock Market.Taking composite index in stock market as the sample, the paper analyzes long memory and non-symmetry in volatilities of Chinese stock returns, explanations of trade volume to price fluctuation, influence of investors on price fluctuation, drawing a follow conclusion:A great many researches on long memory in volatilities of Chinese stock returns thinks that volatilities of Shenzhen stock market have most noticeable long memory, but there is no consensus as whether volatilities of Shanghai stock market have long memory. Taking the Shanghai Composite Index as the sample, Chapter 3 employs the FIGARCH and the FIPARCH models to investigate the long memory in volatilities of Chinese stock returns. The findings from the 2 models show that the volatilities in the log series of the returns of the Shanghai securities market have obviously long memory.Leverage effect in volatilities of stock market refers to:"Bad News"and"Good News"have non-symmetrical influences on stock market; fluctuation in stock market as to"Bad news"is more violent than"good news". Taking composite index of seven nations (including Shanghai Composite Index and the Shenzhen Component Index) as samples, Chapter 4 employs EGARCH models to research into the non-symmetry of price fluctuation in China's stock markets and the differences between this non-symmetry and mature market. We find that, this non-symmetry is very weak compared with mature market, probably because of special structure of china's stock market and loan interest rate lacking of rigidity.Mix distribution hypnoses assume that the asset price movement and the trading volume are both determined by an unobservable flow of information; different pieces of information flowing into the security market will cause movements of both the trading volume and the price. Taking the composite index of 8 nations as the samples, chapter five analyses the differences between explanations of trading volume of China'stock to price fluctuation and mature market. We find that, in US security market, price fluctuation can be explained well by trading volume; but CAC 40 index of France, DAX index of Germany, NIKKEI 225 index of Japan, Swiss index of Swiss, STI Index of Singapore can only be explained by volume series; volume series is the weakest to explain price fluctuation of China's stock market.At present, overseas theories and its empirical study have no agreement in relationships between institutional investors and market fluctuation, but some researchers at home think those investors doesn't stabilize market, and some empirical studies think institutional investors are conducive to reduce fluctuations. Taking the daily returns of the Shanghai Composite Index and the Shenzhen Component Index as samples, Chapter 6 employs GARCH and EGARCH models to research into the influence of the institutional investors on the return variability of China's stock markets. The empirical evidences reveal that institutional investors'extensive entry into the stock markets has decreased the return variability, enhanced its stability and reduced the leverage effect on the return variability. This finding shows that institutional investors can effectively bring down the return variability of the stock market.
Keywords/Search Tags:Market Microstructure, Volatility, Long Memory, Non-symmetry, GARCH Model, EGARCH Model, Trading Volume, Intuitional Investors
PDF Full Text Request
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