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

Takashi Yamashita, Kotaro Hirasawa, Jinglu Hu

Research output: Contribution to conferencePaper

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 languageEnglish
Pages2057-2062
Number of pages6
Publication statusPublished - 2005 Dec 1
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: 2005 Aug 82005 Aug 10

Conference

ConferenceSICE Annual Conference 2005
CountryJapan
CityOkayama
Period05/8/805/8/10

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.