Abstract:To investigate the co-movement of stock, traditional time series analysis and data mining technology mainly use domestic or foreign stock index to study the co-movement bet ween market, sector or industry, and obtain some macroscopic conclusion. Therefore, there is a lack of direct analysis and mining linkage between individual stocks data issues. A method based on dynamic time warping is proposed to analyze the co-movement between two individual stocks. It can find some similar stocks in shape and obtain relevant essential information from extra-large stocks. Combining with k-means clustering method based on dynamic time warping, the clustering method can gain some clusters which have the same fluctuation tendency. The results demonstrate that the proposed method can accurately find the stocks which have linkage relationship from large amounts of stocks, as well as separating clusters of different fluctuation of stocks. It shows that the proposed method has a certain superiority.