Stock Price Prediction and Trend Prediction Using Neural Networks

In this paper, I analyzed feed forward network using back propagation learning method with early stopping and radial basis neural network to predict the trend of stock price (i.e. classification) and to predict the stock price (i.e. value prediction). Fundamental data or Technical indicators were not used in this research as basic objective of this research was to determine the usability of artificial neural networks in predicting the future prices based on past prices alone.

[1]  Clarence N. W. Tan.  Trading a NYSE-stock with a simple artificial neural network-based financial trading system , 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[2]  H. S. Ng,et al.  Intraday stock price analysis and prediction , 2000, Proceedings of the 2000 IEEE International Conference on Management of Innovation and Technology. ICMIT 2000. 'Management in the 21st Century' (Cat. No.00EX457).

[3]  Clarence N. W. Tan,et al.  A study of the parameters of a backpropagation stock price prediction model , 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[4]  Ying-Hua Lu,et al.  Center selection for RBF neural network in prediction of nonlinear time series , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[5]  K. Sakakibara,et al.  Stock Price Forecasting using Back Propagation Neural Networks with Time and Profit Based Adjusted Weight Factors , 2006, 2006 SICE-ICASE International Joint Conference.