Structural learning of neural networks for forecasting stock prices

Junzo Watada

Structural learning of neural networks for forecasting stock prices

Junzo Watada^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Generally, a neural network spends much computation time and cost in forecasting the value and movement of a stock. The reason is because a neural network requires exponential time in computation according to the number of units in a hidden layer. The objective of the paper is to optimally build a neural network through structurally learning. The results enable us to reduce the computational time and cost as well as to understand the structure more easily. In the paper the method is employed in forecasting the price movement of a stock. The optimization of the network by the structured learning is evaluated based on its real use.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	972-979
Number of pages	8
Volume	4253 LNAI - III
Publication status	Published - 2006
Event	10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 - Bournemouth Duration: 2006 Oct 9 → 2006 Oct 11

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4253 LNAI - III
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006
City	Bournemouth
Period	06/10/9 → 06/10/11

Keywords

Forecasting the stock
Structural learning

ASJC Scopus subject areas

Computer Science(all)
Biochemistry, Genetics and Molecular Biology(all)
Theoretical Computer Science

Cite this

Watada, J. (2006). Structural learning of neural networks for forecasting stock prices. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4253 LNAI - III, pp. 972-979). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4253 LNAI - III).

Structural learning of neural networks for forecasting stock prices. / Watada, Junzo.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4253 LNAI - III 2006. p. 972-979 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4253 LNAI - III).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Watada, J 2006, Structural learning of neural networks for forecasting stock prices. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4253 LNAI - III, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4253 LNAI - III, pp. 972-979, 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006, Bournemouth, 06/10/9.

Watada J. Structural learning of neural networks for forecasting stock prices. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4253 LNAI - III. 2006. p. 972-979. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Watada, Junzo. / Structural learning of neural networks for forecasting stock prices. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4253 LNAI - III 2006. pp. 972-979 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Structural learning of neural networks for forecasting stock prices

Abstract

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Keywords

ASJC Scopus subject areas

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