Algorithms comparison on intraday index return prediction:evidence from China

We introduce the fading memory recursive least squares (FM-RLS) and rolling window ordinary least squares (RW-OLS) methods to predict CSI 300 intraday index return in Chinese stock market. Empirical results show that the performances are better than that of same sign method. The additional profit is mainly from two conflict signals, with one amplitude far greater than the other.

Automated summary

Introducing FM-RLS and RW-OLS methods for predicting CSI 300 intraday index return in the Chinese stock market showed better performance than the same sign method. The additional profit mainly comes from two conflicting signals, with one amplitude far greater than the other.