Hybrid Intelligent Systems for Stock Market Analysis
The use of intelligent systems for stock market predictions has been widely established. This paper deals with the application of hybridized soft computing techniques for automated stock market forecasting and trend analysis. We make use of a neural network for one day ahead stock forecasting and a neuro-fuzzy system for analyzing the trend of the predicted stock values. To demonstrate the proposed technique, we considered the popular Nasdaq-100 index of Nasdaq Stock MarketSM. We analyzed the 24 months stock data for Nasdaq-100 main index as well as six of the companies listed in the Nasdaq-100 index. Input data were preprocessed using principal component analysis and fed to an artificial neural network for stock forecasting. The predicted stock values are further fed to a neuro-fuzzy system to analyze the trend of the market. The forecasting and trend prediction results using the proposed hybrid system are promising and certainly warrant further research and analysis.
- Kasabov N and Qun Song, Dynamic Evolving Fuzzy Neural Networks with ‘m-out-of-n’ Activation Nodes for On-line Adaptive Systems, Technical Report TR99/04, Department of information science, University of Otago, 1999.Google Scholar
- Duszak Z and Loczkodaj W W, Using Principal Component Transformation in Machine Learning, Proceedings of International Conference on Systems Research, Informatics and Cybernetics, Baden-Baden Germany, p.p 125–129, 1994.Google Scholar
- Zadeh LA, Roles of Soft Computing and Fuzzy Logic in the Conception, Design and Deployment of Information/Intelligent Systems, Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications, O Kaynak, LA Zadeh, B Turksen, IJ Rudas (Eds.), pp1–9, 1998.Google Scholar
- Abraham A & Nath B, Designing Optimal Neuro-Fuzzy Systems for Intelligent Control, In proceedings of the Sixth International Conference on Control Automation Robotics Computer Vision, (ICARCV 2000), Singapore, December 2000.Google Scholar
- Cherkassky V, Fuzzy Inference Systems: A Critical Review, Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications, Kayak O, Zadeh LA et al (Eds.), Springer, pp.177–197, 1998.Google Scholar