Abstract
Elman Neural Network is a typical regression nerve network which is highly applicable in processing sequential data. In order to predicate accuratelythe fluctuation of stock prices, Elman Neural Network is applied in the forecast of the opening price of SSE (Shanghai Stock Exchange). This paper establishes mathematical models for the input layer, the hidden layer, connection layer and the output layer based on Elman Neural Network. The opening prices of SSE of 337 trading days from December, 2012 to April, 2014 are selected as the raw data for stimulated forecast, and its result proves the validity of this forecast model.
