Application of neural sequential associator to long-term stock price prediction
- Resource Type
- Conference
- Authors
- Matsuba, I.
- Source
- [Proceedings] 1991 IEEE International Joint Conference on Neural Networks Neural Networks, 1991. 1991 IEEE International Joint Conference on. :1196-1201 vol.2 1991
- Subject
- Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Neural networks
Multi-layer neural network
Neurons
Artificial neural networks
Feature extraction
Data mining
Laboratories
Parameter estimation
Delay effects
Pattern recognition
- Language
A neural sequential associator using feedback multilayer neural networks in duplicate is proposed to analyze the inherent structure in the sequence and to predict the future sequence based on this structure. It is shown that the present method gives a better performance than that of neural networks without feedback when applied to the prediction of long-term stock prices.ETX