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 …

A neuro-evolutionary method for a short-term stock index prediction is presented. The data is
gathered from the German stock exchange (the target market) and two other markets (Tokyo …

A neural network system developed for forecasting stock prices in the Japanese market is
presented. The hybrid algorithm, which combines the modified BP (backpropagation) …

We propose an intelligent stock trading decision support system that can forecast the buying
and selling signals according to the prediction of short-term and long-term trends using rule …

Reports on the use of artificial neural networks to forecast the performance of the Stock
Exchange of Singapore. Positive correlation of the stocks to the movement of the Straits …

Forecasting stock exchange rates is an important financial problem that is receiving
increasing attention. During the last few years, a number of neural network models and …

This paper describes an evolutionary neural network approach to Hang Seng stock index
forecast. In this approach, a feedforward neural network is evolved using an evolutionary …

In recent years, many attempts have been made to predict the behavior of bonds, currencies,
stocks, or stock markets. The Standard and Poors 500 Index is modeled using different …

Price index forecasting is one of the most important problems in financial markets. In the past
decades the prediction of stock index has played a vital role in the financial situation of …

Stock index forecast is not an easy job as it is subject to influence of various factors. Since
1980s, many researchers have used Back Propagation Neural Network BPNN to forecast …