Time series prediction system of stock price using multi-branch neural networks

Takashi Yamashita*, Kotaro Hirasawa, Jinglu Hu

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review


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 languageEnglish
Number of pages6
Publication statusPublished - 2005
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: 2005 Aug 82005 Aug 10


ConferenceSICE Annual Conference 2005


  • 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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