Title :
Training neural network with genetic algorithms for forecasting the stock price index
Author :
Kai, Fu ; Wenhua, Xu
Author_Institution :
Bank of China, Hebei, China
Abstract :
The paper combines genetic algorithms (GA) with neural network (NN). It trains NN with GA and then predicts the stock price index with the trained network. By learning the special stock knowledge, it can find out the modes and relationship hidden in the abstract data. It can help shareholders and investment agencies to make wise decisions in the stock market so as to get more profits. The primary data are from Shanghai Stock Exchange from March 29, 1994 to August 1, 1994. The imitation result shows that the network is fit for short time prediction and it has high precision
Keywords :
forecasting theory; genetic algorithms; investment; learning (artificial intelligence); neural nets; stock markets; Shanghai Stock Exchange; abstract data; genetic algorithms; investment agencies; neural network training; shareholders; short time prediction; special stock knowledge; stock price index forecasting; Content management; Economic forecasting; Expert systems; Genetic algorithms; Industrial training; Investments; Macroeconomics; Neural networks; Production; Stock markets;
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
DOI :
10.1109/ICIPS.1997.672809
