Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Classifier fitness based on accuracy
Evolutionary Computation
Neural networks in financial engineering: a study in methodology
IEEE Transactions on Neural Networks
A bootstrap evaluation of the effect of data splitting on financial time series
IEEE Transactions on Neural Networks
On-line learning algorithms for locally recurrent neural networks
IEEE Transactions on Neural Networks
Forecasting the volatility of stock price index
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
A neural network ensemble method with jittered training data for time series forecasting
Information Sciences: an International Journal
Using multiple indexes for efficient subsequence matching in time-series databases
Information Sciences: an International Journal
Adaptive signal processing of asset price dynamics with predictability analysis
Information Sciences: an International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Obtaining transparent models of chaotic systems with multi-objective simulated annealing algorithms
Information Sciences: an International Journal
Evolving neural networks for static single-position automated trading
Journal of Artificial Evolution and Applications - Regular issue
Path planning on a cuboid using genetic algorithms
Information Sciences: an International Journal
Inventory lot-sizing with supplier selection using hybrid intelligent algorithm
Applied Soft Computing
Expert Systems with Applications: An International Journal
Fidelity-guaranteed robustness enhancement of blind-detection watermarking schemes
Information Sciences: an International Journal
Short-term stock price prediction based on echo state networks
Expert Systems with Applications: An International Journal
Surveying stock market forecasting techniques - Part II: Soft computing methods
Expert Systems with Applications: An International Journal
A neural network with a case based dynamic window for stock trading prediction
Expert Systems with Applications: An International Journal
Forecasting stock market short-term trends using a neuro-fuzzy based methodology
Expert Systems with Applications: An International Journal
An artificial neural network (p,d,q) model for timeseries forecasting
Expert Systems with Applications: An International Journal
Financial market trading system with a hierarchical coevolutionary fuzzy predictive model
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Time Series Forecasting Using Hybrid Neuro-Fuzzy Regression Model
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
MISMIS - A comprehensive decision support system for stock market investment
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
A locally linear RBF network-based state-dependent AR model for nonlinear time series modeling
Information Sciences: an International Journal
Evaluation approach to stock trading system using evolutionary computation
Expert Systems with Applications: An International Journal
Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
Information Sciences: an International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A dynamic threshold decision system for stock trading signal detection
Applied Soft Computing
Information Sciences: an International Journal
A new class of hybrid models for time series forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Forecasting the volatility of stock price index
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Adaptive stock trading with dynamic asset allocation using reinforcement learning
Information Sciences: an International Journal
Financial time series forecasting with a bio-inspired fuzzy model
Expert Systems with Applications: An International Journal
International Journal of Productivity Management and Assessment Technologies
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
Hybrid Kansei-SOM model using risk management and company assessment for stock trading
Information Sciences: an International Journal
Identification of stock market forces in the system adaptation framework
Information Sciences: an International Journal
Fuzzy artificial neural network p, d, q model for incomplete financial time series forecasting
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In this paper, a new approach for time series forecasting is presented. The forecasting activity results from the interaction of a population of experts, each integrating genetic and neural technologies. An expert of this kind embodies a genetic classifier designed to control the activation of a feedforward artificial neural network for performing a locally scoped forecasting activity. Genetic and neural components are supplied with different information: The former deal with inputs encoding information retrieved from technical analysis, whereas the latter process other relevant inputs, in particular past stock prices. To investigate the performance of the proposed approach in response to real data, a stock market forecasting system has been implemented and tested on two stock market indexes, allowing for account realistic trading commissions. The results pointed to the good forecasting capability of the approach, which repeatedly outperformed the "Buy and Hold" strategy.