The use of intelligent systems for stock market predictions has been widely established. In
this paper, we introduce a genetic programming technique (called multi-expression …

The use of intelligent systems for stock market predictions has been widely established. This
chapter introduces two Genetic Programming (GP) techniques: Multi-Expression …

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 …

The use of intelligent systems for stock market predictions has been widely established. This
paper introduces a genetic programming technique (called Multi-Expression programming) …

The use of intelligent systems for stock market predictions has been widely established. This
paper introduces a ensemble model of SVM and ANNs for the prediction of three stock …

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm
(GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators …

Applications of learning algorithms in knowledge discovery are promising and relevant area
of research. It is offering new possibilities and benefits in real-world applications, helping us …

The use of neural networks (NNs) for stock market forecast is quite common because of their
excellent performances of treating non-linear data with self-learning capability. However …

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 …