Characters Of Stock Volatility In Shanghai And Shenzhen Markets And The Relationship Between Volatility And Trading Volume

Accurately estimating volatility is important for investment, risk management, policy making. The second purpose of this paper is to study the asymmetric relationship between volatility and trading volume. By comparing different models synthetically, it can help us have an insight into volatility in stock markets. The studying about asymmetric effect provide an intuitively view on leverage effect.By comparing, it indicates that EGARCH-N-L.V model has a good forecasting ability. Although by assuming the return with a student's t distribution or generalized error distribution the GARCH-type models will fit the data well, it doesn't improve forecasting ability. Under normal distributional assumption EGARCH-N-L.V shows better modeling ability.Conventionally, trading volume is used to study the effect on volatility persistence. But this effect is not significantly in China's stock markets. Hence, I use trading volume to study the asymmetric relationship with volatility. I consider the volatility clustering of unexpected trading volume. It shows that asymmetrical effect of market information can be largely represented by trading volume. The relationship between volatility and trading volume show us not only how large the effect is but also the direction of the effect.