An Investigation Of The Hybrid Forecasting Models For Stock Price Variation In Taiwan

Journal of the Chinese Institute of Industrial Engineers

Volumn 21, Issue 4, 2004, Pages 358-368

  Chang, Pei Chann ^a   Wang, Yen Wen ^a   Yang, Wen Ning ^a  

^a YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Autoregressive integrated moving average models; Backpropagation neural networks; Multiple regression analysis

Indexed keywords

COST ACCOUNTING; INDUSTRIAL ECONOMICS; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS;

AUTOREGRASSIVE INTEGRATED MOVING AVERAGE MODELS; BACKPROPAGATION NEURAL NETWORKS; MULTIPLE REGRESSION ANALYSIS;

FORECASTING;

EID: 24644515811     PISSN: 10170669     EISSN: 21517606     Source Type: Journal    
DOI: 10.1080/10170660409509416     Document Type: Article

References (10)

1. Baba, N., and Kozaki, M., 1992. An intelligent forecasting system of stock price using neural networks. IEEE International Joint Conference on Neural Network, 1:371–377.
2. Chi, S. C., Chen, H. P., and Cheng, C. H., 1999. A forecasting approach for stock index future using grey theory and neural networks. IEEE International Joint Conference on Neural Networks,:3850–3855.
3. Gencay, R., 1996. Nonlinear prediction of security returns with moving average rules. Journal of Forecasting, 15:165–175.
4. Grudnitski, G., and Osburn, L., 1993. Forecasting S&P and gold future prices:An application of neural networks. Journal of Futures Markets, 13(6):631–643.
5. Kamijo, K., and Tanigawa, T., 1990. Stock price pattern recognition-A recurrent neural networks approach. IEEE International Joint Conference on Neural Networks,:215–221.
6. Kimoto, T., and Asakawa, K., 1990. Stock market prediction system with modular neural networks. IEEE International Joint Conference on Neural Networks,:1–6.
7. Kim, K. J., and Han, I., 2000. Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index. Expert Systems with Applications, 19:125–132.
8. Lapedes, A., and Farber, R., 1987. Nonlinear signal proceeding using neural networks:Prediction and system modeling. Los Alamos National Laboratory Report LA-UR-87-2662
9. Lee, J. W., 2001. Stock price prediction using reinforcement learning. IEEE International Joint Conference on Neural Networks,:690–695.
10. Refenes, A. N., Azema-Barac, M., and Zapranis, A. D., 1993. “Stock ranking:Neural networks vs. multiple linear regression”. In International Conference on Neural Networks 1419–1426. San Francisco