In this thesis, we revised and proposed several models and then used them to forecast the stock index. The first model is an improved version of the GM (1, 1) model by introducing two parameters. Then we revised the normal hybrid model G-ARMA by merging the ARMA model with the improved GM (1, 1) model. In order to overcome the drawback of directly modeling original stock index, we introduced wavelet methods into the revised G-ARMA model and named this new hybrid model WG-ARMA. Finally, we obtained the last hybrid model WPG-ARMA by replacing the wavelet transform with the wavelet packet...