An Empirical Study on the Relation between Stock Return and Volatility in the China Stock Markets
中国股票市场的股票收益与波动关系研究

We examine time series features of stock returns and volatility, as well as the relation between returns and volatility in China's stock markets. Firstly, GARCH and EG ARCH models are employed to generate conditional variance series. The application of the two models provides strong evidences of time-varying volatility. In addition, the results show that the time of high and low volatility tends to converge and volatility is highly persistent and predictable. Then we test the relation between expected returns and expected risk with the GARCH-M model. We find that daily trading volume, used as a proxy for information arrival time, has no significant explanatory power on the conditional volatility of daily returns.