A performance comparison of neural networks in forecasting stock price trend

Abstract

The stock price shows the character of complex non-linear system, along with changes of internal and external environmental factors in stock market. As a form of artificial intelligence, neural network can fully reveal the complex relationship between investors and price fluctuations. After comparing network structures of different neural networks, the conclusions show Elman neural network has an obvious advantage over BP neural network in predicting price trend of Chinese stock market both in theory and practice.