Applying Artificial Neural Network And Trading Strategies In The Taiwan Stock Market

• Main Authors: Lo, Ken-Chih, 羅亘志
• Other Authors: Yeou-Ren Shiue
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/34263270783788256369

碩士 === 華梵大學 === 資訊管理學系碩士班 === 100 === In this study, used the recurrent neural network(Elman Recurrent Neural Network) and the back-propagation neural Network (Back-Propagation Neural Network, BPN) to build the model, the Taiwan Securities Exchange(TWSE) cooperation with the Financial Times and Stock Exchange(FTSE) compiling Taiwan 50 Index for the subject, to explore its every other day for the closing of the forecast, then two predictions of the model and operating strategy of a combination of simulated trading research can profit. Research data to the Taiwan Securities Exchange(TWSE) cooperation with the Financial Times and Stock Exchange(FTSE) compiling Taiwan 50 Index, since September 1, 2008 until September 30, 2010 only, a total of 522 document data. Taiwan 50 Index data, and international stock markets, after-hours IT TAIEX combined total of 24 technical indicators, as neural network input variables. From September 1, 2008 to September 30, 2010 total of 522 documents data as training and test data . Elman and analyzed by the BPN, in days, for testing, training, explore the neural network to forecast results and operating strategies combined with the possibility of profit from the stock market. According to experimental results show that the use of neural network prediction predict the Taiwan 50 index closed the next day with the trading strategies simulated trading can be profitable; the use of neural network with the trading strategy in the Taiwan stock market, profit is feasible.