Multi-branch neural networks and its application to stock price prediction

Takashi Yamashita, Kotaro Hirasawa, Jinglu Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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 than conventional NNs. In this paper, a prediction system of a stock price using MBNNs is proposed. Using the stock prices in time series and other information, MBNNs can learn to predict the price of the next day. The result of our simulations shows that the proposed system has better accuracy than a system using conventional NNs.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
PublisherSpringer Verlag
Pages1-7
Number of pages7
ISBN (Print)3540288945, 9783540288947
DOIs
Publication statusPublished - 2005 Jan 1
Event9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
Duration: 2005 Sep 142005 Sep 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3681 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
CountryAustralia
CityMelbourne
Period05/9/1405/9/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Multi-branch neural networks and its application to stock price prediction'. Together they form a unique fingerprint.

  • Cite this

    Yamashita, T., Hirasawa, K., & Hu, J. (2005). Multi-branch neural networks and its application to stock price prediction. In Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings (pp. 1-7). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3681 LNAI). Springer Verlag. https://doi.org/10.1007/11552413_1