Neural network with genetically evolved algorithms for stocks prediction

Abstract

Many studies have shown that artificial neural networks have the capability to learn the underlying mechanics of stock markets. In fact, artificial neural networks have been widely used for forecasting financial markets. However, such applications to Singapore stock markets are scarce. This paper applies genetically evolved neural network models to predict the Straits Times Index (STI) of the Stock Exchange of Singapore (SES). Our studies show that satisfactory results can be achieved when applying genetically evolved neural networks to predict the STI.