Modelling and forecasting the stock market volatility of SSE Composite Index using GARCH models

The result shows that from the time series point of view, the SSE Composite Index possesses significant properties of time-varying and clustering. Series distribution of it presents leptokurtosis with significant ARCH and GARCH effects. Moreover, by comparing the fitting and forecast performance of GARCH (1, 1) (symmetric) and TARCH (1, 1) and EGARCH (1, 1) (asymmetric), it can be concluded that EGARCH (1, 1) outperforms the others. Besides, China's securities market should strengthen its system construction, reduce excessive government intervention and advocate rational investment philosophy.