Abstract
Recently, artificial neural networks have been utilized for financial market applications. We have so far shown that multi-branch neural networks (MBNNs) could have higher representation and generalization ability. In this paper, a prediction system of a stock price using MBNNs is proposed. The result of our simulations shows that the proposed system has better accuracy than a system using conventional NNs.
| Original language | English |
|---|---|
| Pages | 2057-2062 |
| Number of pages | 6 |
| Publication status | Published - 2005 Dec 1 |
| Event | SICE Annual Conference 2005 - Okayama, Japan Duration: 2005 Aug 8 → 2005 Aug 10 |
Conference
| Conference | SICE Annual Conference 2005 |
|---|---|
| Country | Japan |
| City | Okayama |
| Period | 05/8/8 → 05/8/10 |
Keywords
- Multi-branch
- Neural networks
- Stock price prediction
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering
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Cite this
Yamashita, T., Hirasawa, K., & Hu, J. (2005). Time series prediction system of stock price using multi-branch neural networks. 2057-2062. Paper presented at SICE Annual Conference 2005, Okayama, Japan.