This study investigates five competing time series econometric models with high-frequency data on CSI300 Index and CSI300 Index Futures. For the estimation of the optimal hedge ratio and compare their effectiveness with that of other hedging models, including the naive, the conventional static, the constant conditional correlation (CCC) GARCH, the dynamic conditional correlation (DCC) GARCH, and the asymmetric dynamic conditional correlation (ADCC) GARCH models. With regard to the reduction of variance in the returns of hedged portfolios, the results clearly show that the CCC GARCH and the ADCC GARCH have higher mean return and higher average variance reduction across hedged and unhedged positions in the in- sample and out-of-sample. In CSI300 stock index futures, the hedge ratio from ADCC GARCH model provides greater variance reduction in out-of-sample. These findings are helpful to risk managers dealing with China stock index futures.