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Study Of The Chinese Stock Market Volatility

Posted on:2002-01-10Degree:MasterType:Thesis
Country:ChinaCandidate:Z Z ChenFull Text:PDF
GTID:2206360032954822Subject:Quantitative Economics
Abstract/Summary:PDF Full Text Request
Throughout a decade development of China Stock Market ,the stock price fluctuates violently and frequently .Though we can not deny the positive effect of the high volatility in the early development of China Stock Market ,the negative effect of the extremely high volatility should draw more attention .In fact ,the government has always been trying to keep the level of stock market volatility in a reasonable range .This paper is aimed to delve the basic factor that induces the high volatility of China Stock Market and reveal some quantitative characteristics of China Stock Market volatility.This paper is divided into four chapters .The content and viewpoints are summarized as follows:Chapter One is a brief analysis of the volatility of China Stock Market from the perspective of new institutional economics .The stock price fluctuation is determined by the behavior pattern of participants of the stock market ,so we can attribute the extremely high volatility of China Stock Market to the abnormal behavior of participants of China Stock Market .According to the new institutional economics ,the abnormal behavior of participants of stock market results from institutional drawbacks of stock market ,which is the basic factor to cause the extremely high volatility of China Stock Market ,and so institutional innovation is the basic way to control the level of volatility in a reasonable range.Chapter Two uses the Impulse Response Function and Forecast Error Variance Decomposition in VAR analysis to determine the persistence of the effect of stock market shocks on the volatility .The volatility of Shanghai Stock Market and Shenzhen Stock Market are put in a first order VAR model to estimate the Impulse Response Function and decompose the forecast error variance .The estimated Impulse Response Function converges to 0 and the Forecast Error Variance Decomposition converges to a constant value in 6 to 7 months or so ,which indicates that the effect of a stock market shock on the volatility would die out about 6 to 7 months after the shock happened.Chapter Three Examines the relationship between Stock Market volatility and the volatility of a set of macroeconomic variables .According to the present value model of stock price ,that is ,the current stock price is the discounted present value of expected future cash flows ,we can infer that a change in the level of uncertainty about future macroeconomic conditions would cause a proportional change in stock volatility .From the perspective of econometrics ,macroeconomic volatility is Granger caused by the stock market volatility .First ,the pairwise Granger cause test between the stock market volatility and the volatility of Value-added of Industry and broad money M2 and Inflation is conducted .Second ,the stock market volatility and the three macroeconomic volatility are put in VAR models to conduct Granger cause test .All the tests show that there is no significant Granger cause relationship between the stock market volatility and the macroeconomic volatility .So ,information contained in the past history of stock market volatility can not help to forecast the macroeconomic volatility.Chapter Four focuses on a particular characteristic of the stock market volatility .Most of financial asset returns including stock return have time varying volatility ,which can be well depicted by the ARCH model and its various extended forms .First ,LM test and Q statistic test are conducted for the Composite Index of Shanghai Stock Exchange and the Component Index of Shenzhen Stock Exchange ,the null hypothesis of constant volatility is rejected ,so the volatility of China Stock Market is not constant over time .Second ,GARCH(1,1) model ,IGARCH(1,1) model ,GARCH-M model and EGARCH model are estimated respectively to examine the stationarity of stock market volatility ,the relation of stock market volatility with stock return and the asymmetric effect of stock market volatility .The estimated GARCH(1,1) model indicates that the volatility of China Stock Market is wide-sense stationa...
Keywords/Search Tags:stock market volatility, institution, persistence, Impulse Response Function, Forecast Error Variance Decomposition, Granger cause, time varying volatility, ARCH model
PDF Full Text Request
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