Stock data analysis based on Hilbert-Huang transform

For adaptively analyzing non-stationary and nonlinear signals, Hilbert-Huang Transform (HHT) has recently been pioneered by Huang et al. In this paper, new stock prices of the prediction model is presented by combining the Hilbert-Huang transform. Intrinsic Mode Functions in the low frequency parts are obtained to replace the traditional motive average lines to analyze stock prices. The simulation results show that the proposed method gives the price better than those by traditional methods do.