# Combining Selective-Presentation and Selective-Learning-Rate Approaches for Neural Network Forecasting of Stock Markets

### Kazuhiro Kohara

#### 2008

#### Abstract

We have investigated selective learning techniques for improving the ability of back-propagation neural networks to predict large changes. We previously proposed the selective-presentation approach, in which the training data corresponding to large changes in the prediction-target time series are presented more often, and selective-learning-rate approach, in which the learning rate for training data corresponding to small changes is reduced. This paper proposes combining these two approaches to achieve fine-tuned and step-by-step selective learning of neural networks according to the degree of change. Daily stock prices are predicted as a noisy real-world problem. Combining these two approaches further improved the performance.

#### References

- Weigend, A., Huberman, B., Rumelhart, D.: Predicting the future: a connectionist approach. International Journal of Neural Systems, Vol. 1, No. 3. (1990) 193-209
- Vemuri, V., Rogers, R. (eds): Artificial Neural Networks: Forecasting Time Series. IEEE Press, Los Alamitos, CA (1994)
- Pham, D., Liu, X.: Neural Networks for Identification, Prediction and Control. Springer (1995)
- Kil, D., Shin, F.: Pattern Recognition and Prediction with Applications to Signal Characterization. American Institute of Physics Press (1996)
- Mandic, D., Chambers, J.: Recurrent Neural Networks for Prediction. John Wiley & Sons (2001)
- Azoff, E.: Neural Network Time Series Forecasting of Financial Markets. John Wiley and Sons, West Sussex (1994)
- Refenes, A., Azema-Barac, M.: Neural network applications in financial asset management. Neural Computing & Applications, Vol. 2, No. 1. Springer-Verlag, London (1994) 13-39
- White, H.: Economic prediction using neural networks: the case of IBM daily stock return. Proceedings of International Conference on Neural Networks. San Diego, CA (1988) II451-II-458
- Baba, N., Kozaki, M.: An intelligent forecasting system of stock price using neural networks. Proceedings of International Conference on Neural Networks. Singapore (1992) I371-I-377
- Freisleben, B.: Stock market prediction with backpropagation networks. Lecture Notes in Computer Science, Vol. 604. Springer-Verlag, Heidelberg (1992) 451-460
- Tang, Z., Almeida, C., Fishwick, P.: Time series forecasting using neural networks vs. BoxJenkins methodology. Simulation, Vol. 57, No. 5. (1991) 303-310
- Kohara, K., Fukuhara, Y., Nakamura, Y.: Selective presentation learning for neural network forecasting of stock markets. Neural Computing & Applications, Vol. 4, No. 3. SpringerVerlag, London (1996) 143-148
- Kohara, K., Fukuhara, Y., Nakamura, Y.: Selectively intensive learning to improve largechange prediction by neural networks. Proceedings of International Conference on Engineering Applications of Neural Networks. London (1996) 463-466
- Kohara, K.: Selective-learning-rate approach for stock market prediction by simple recurrent neural networks. Lecture Notes in Artificial Intelligence, Vol. 2773. Springer-Verlag, Heidelberg, (2003) 141-147
- Kohara, K.: Neural networks for economic forecasting problems. In: Cornelius T. Leondes (ed): Expert Systems -The Technology of Knowledge Management and Decision Making for the 21st Century-. Academic Press. San Diego, CA (2002)
- Kohara, K.: Foreign Exchange Rate Prediction with Selective Learning BPNNs and SOMs. Proceedings of World Multi-Conference on Systemics, Cybernetics and Informatics. Orland, FL (2005) 350-354
- Park, D., El-Sharkawi, M., Marks II, R., Atlas, L., Damborg, M.: Electric load forecasting using an artificial neural network. IEEE Transactions on Power Systems. Vol. 6, No. 2. (1991) 442-449

#### Paper Citation

#### in Harvard Style

Kohara K. (2008). **Combining Selective-Presentation and Selective-Learning-Rate Approaches for Neural Network Forecasting of Stock Markets** . In *Proceedings of the 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2008)* ISBN 978-989-8111-33-3, pages 3-9. DOI: 10.5220/0001508200030009

#### in Bibtex Style

@conference{anniip08,

author={Kazuhiro Kohara},

title={Combining Selective-Presentation and Selective-Learning-Rate Approaches for Neural Network Forecasting of Stock Markets},

booktitle={Proceedings of the 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2008)},

year={2008},

pages={3-9},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0001508200030009},

isbn={978-989-8111-33-3},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2008)

TI - Combining Selective-Presentation and Selective-Learning-Rate Approaches for Neural Network Forecasting of Stock Markets

SN - 978-989-8111-33-3

AU - Kohara K.

PY - 2008

SP - 3

EP - 9

DO - 10.5220/0001508200030009