Turning point identification and Bayesian forecasting of a volatile time series
Computers and Industrial Engineering
A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
Software—Practice & Experience
An introduction to econophysics: correlations and complexity in finance
An introduction to econophysics: correlations and complexity in finance
Genetic Programming Prediction of Stock Prices
Computational Economics
Explorations in LCS Models of Stock Trading
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Nonlinear feature extraction using a neuro genetic hybrid
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Financial volatility trading using recurrent neural networks
IEEE Transactions on Neural Networks
A stock recommendation system exploiting rule discovery in stock databases
Information and Software Technology
Neuro-genetic system for stock index prediction
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
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In this paper, we propose a neuro-genetic stock prediction system based on financial correlation between companies. A number of input variables are produced from the relatively highly correlated companies. The genetic algorithm selects a set of informative input features among them for a recurrent neural network. It showed notable improvement over not only the buy-and-hold strategy but also the recurrent neural network using only the input variables from the target company.