Stock market prediction is important and of great interest because successful prediction of
stock prices may promise attractive benefits. These tasks are highly complicated and very …

One of the major problems the finance domain faces is the uncertain and nonlinear changes
in data with respect to time. There is an urgent necessity to tackle such time-dependent …

Stock price prediction has drawn huge attention due to its impact on economic stability.
Accurate stock price prediction is highly essential to reduce the risk associated with it so as …

The search for patterns or motifs in data represents a problem area of key interest to finance
and economic researchers. In this paper, we introduce the motif tracking algorithm (MTA), a …

Genetic Programming (GP) is an automated method for creating computer programs starting
from a high-level description of the problem to be solved. Many variants of GP have been …

Genetic programming (GP) and its variants have been extensively applied for modeling of
the stock markets. To improve the generalization ability of the model, GP have been …

This paper presents an application of the gene expression programming (GEP) and
integrated genetic programming (GP) algorithms to the modelling of ASE 20 Greek index …

Time series identification is one of the key approaches to dealing with time series data and
discovering the change rules. Therefore, time series forecasting can be treated as one of the …

This paper presents an intelligent model for stock market signal prediction using Multi-Layer
Perceptron (MLP) Artificial Neural Networks (ANN). Blind source separation technique, from …

This paper presents an efficient system for accurate, confident, general and responsive stock
market prediction, employing Artificial Neural Networks (ANN). For technical indicators, Multi …