Technical analysis has always played a important role in analyzing the capital market. With the rapid development of artificial intelligence, using machine-learning methods for financial applications has become a hot trend. Using a decade of TAIEX as data, adopting a variety of technical analysis indicators as sample set in the research, I compared the precision of LSTM and RNN and GRUconfusion matrix in the deep- learning field by Walk Forward Test and normalization. Finally I get good results about determining direction of increase or decrease price. To prove that The feasibility of applying deep learning method to TAIEX,And discuss the application of different deep learning algorithms to time series.