The Volatility Of China’s Stock Market And Its Relationship With Trading Volume

In order to analysis the volatility features of China’s stock market and how the marketinformation drive the market volatility, this paper bases on the Conditional AutoregressiveRange (CARR) model given by Chou (2005), expands the distribution of the random errorterm to generalized gamma distribution, and proposes a GCARR-X model which can bringin some exogenous variables. Based on the information theory, we use this model to studythe market microstructure of the market volatility driven by the volume, then verify theeffectiveness of technical analysis. Based on the above, we can make the policy for thestock market’s healthy development and strategies for improving investors’ investmentincome.This paper first reviews the literature of volatility in securities markets, brieflyintroduces the characteristics and influencing factors of volatility in the stock market,while describes the relationship between volatility and trading volume from the technicalanalysis and information theoretical model. After that, we tease out the modeling idea ofCARR model, summarize the development of the model, and give the GCARR-X model,which introduces the trading volume as an exogenous variable. Based on the above model,we take the real data of China’s stock market during the financial crisis to research China’sShanghai and Shenzhen stock market volatility and its relationship with the trading volumeempirically.The empirical results show that the GCARR model can well depict the characteristicsof market volatility, the generalized gamma distribution as a more general distribution iscloser to the real distribution of the Shenzhen Component Index’s range; the CARR-Xmodels are suitable for the study of the relationship between market volatility and tradingvolume. Discovered through the research that the volatility of China’s Shanghai andShenzhen stock market shows obvious persistence and asymmetry; trading volume has astrong explanation of the asymmetry of stock market volatility, while this explanationcomes out of the unexpected trading volume, indicating that the stock market volatility caused by the new market information, rather than historical information; for thepersistence of stock market volatility, the rate of return can make some explanation,however, the trading volume gives no further explanation; through the nonlinear CARR-Xmodel, we find that Shenzhen Component Index shows an asymmetry of the tradingvolume on the market fluctuations.