中國(guó)股市股指收益結(jié)構(gòu)性變點(diǎn)與波動(dòng)性建模.pdf

1、山西財(cái)經(jīng)大學(xué)碩士學(xué)位論文中國(guó)股市股指收益結(jié)構(gòu)性變點(diǎn)與波動(dòng)性建模姓名：孫小冬申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：統(tǒng)計(jì)學(xué)指導(dǎo)教師：王建華2011-05-12中國(guó)股市股指收益結(jié)構(gòu)性變點(diǎn)與波動(dòng)性建模 II Abstract Chinese stock market, an emerging market with only 20 years' history, is apt to be influenced by various outside f

2、actors and shows a great fluctuation in result of our imperfect market mechanism, lagged legal system and immature psychology of investors and so on. Therefore, the intensive study of its fluctuations becomes especially

3、important, and many scholars delve into modeling volatility for share indices returns. The development of modeling volatility has gone through three major stages: the early traditional econometric model under the assumpt

4、ion of fixed variance, later AutoRegressive Conditional Heteroskedasticity (ARCH) model and Stochastic Volatility (SV) model, and newly developmental non-parameter model for high-frequency data. Now the most widely used

5、model is still (G)ARCH-type models, but in the practical application, this model could be combined with structural breaks in time series. On this basis, this paper applies dummy variable of structural breaks in GARCH-typ

6、e models, aims to fit the return series of Shanghai Composite Index and Shenzhen Component Index (which from Dec. 16, 1996 to May 31, 2010). The content mainly contains two aspects: Firstly, detect the structural breaks

7、in variance from two sample series with ICSS algorithm, the essence of which is to construct suitable statistics with a series of recursive residuals, and then simulates its distribution and critical value for hypothesis

8、 test. Secondly, put the change-points as dummy variables into GARCH model to re-fit them, pose a contrast of goodness of fit, degree of forecast in all circumstances to select the optimal one. There are extra factors ne

9、ed to be considered, including risk premium, asymmetric effect and error distribution, etc. The empirical studies of sample indicate that parts of significant events in Chinese stock market have caused variance of share

10、indices returns some structural breaks. Considering these breaks, it is better to make them as dummy variable to join EGARCH(1,1) model, in which, goodness of fit for t-distribution error is higher while degree of foreca