Shanghai And Shenzhen Stock Market Volatility Leverage Effect And The Transfer Of The Empirical Research

The responses of investors to unexpected returns and information transmission in the stock markets are investigated by many economists. They find that the stock market returns are characterized by excess kurtosis, volatility clustering, leverage effects and co-movement. Whether this conclusion applies to Chinese case is the main concern of this paper. I analyze the return volatility of Chinese stock market by employing Generalized Asymmetric Power GARCH Model and find the impact of bad news to future volatility is greater than that of good news of the same magnitude in both Shanghai and Shenzhen stock market, consistent with the previous literature. The result also suggests that Leverage GARCH Model fits best. Further this study examines the transmission of return volatility between these two markets. The results of Granger Causality Test and Vector Autoregressive Model indicate Shanghai and Shenzhen stock markets are closely related and the forecast error of one market can be reduced by considering two markets simultaneously.The paper is structured as follows.I begin in section 1 with a brief overview of the stylized characteristics of financial time series and the importance of explicitly modeling return volatility .In section 2, I detail some of the important theoretical developments on the parameterization and the implementation of ARCH-type models.Section 3 makes a literature review on the subject of leverage effect and the intra-market transmission of conditional volatility. For the domestic researches, I introduce the main conclusions and suggest some defects as well. For the foreign researches, the different approaches of some important papers are focused.Section 4 describes the index data to be used in this paper and presents the empirical results. Parameter estimates for the Generalized APARCH model are presented, as are the results of the wald testing procedure. The asymmetric effect is analyzed by employing news impact curves. Finally, the transmission of conditional volatility across markets is studied, using Granger causality test and VAR model. The results suggest there are some feedback relationships between Shanghai and Shenzhen stock market, although the interaction is not as strong as expected.