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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 7
2126-2133

Stock price prediction based on dynamic heterogeneous network

Han Zhongming
Meng Yixin
Guo Huiying
Guo Miaomiao
Mao Yajun
School of Computer & Artificial Intelligence, Beijing Technology & Business University, Beijing 100048, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0568

Abstract

Stock prediction is typically a non-linear time series task. However, few researchers attempt to systematically reveal the underlying structure of the stock market through technical data. The interactions of collaboration or conflicts among various business domains can explain the fluctuations in stock. The incorporation of this additional information aids in predicting the future trends of stocks. In order to represent the trading situation of the stock market as realistically as possible and to express the explicit or implicit relationships between stocks, this paper proposed a stock price prediction model sDHN based on a dynamic heterogeneous network, which synthesized the base of the stock and the industry and geographical information, and modeled it as a dynamic heterogeneous network. The model introduced dynamic time series capabilities to the network, and the algorithm creatively combined four different technical levels of similarity graphs of stock nodes to generate a rich information heterogeneous graph. Finally, it aggregated the semantic information hidden in different meta-paths to generate embeddings, exploring the potential correlations among stocks from the perspective of the heterogeneous graph. In addition, experiments on three real-world stock data sets show that the proposed model achieves accuracy improvements of between 5% and 34% over the overall baseline models. The F1-score is higher by approximately 11.5%~37%. It demonstrates through graphical analysis the effectiveness of this approach.

Foundation Support

国家重点研发计划资助项目(2022YFC3302600)
北京市自然科学基金资助项目(4172016)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0568
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 7
Section: System Development & Application
Pages: 2126-2133
Serial Number: 1001-3695(2024)07-028-2126-08

Publish History

[2024-01-30] Accepted Paper
[2024-07-05] Printed Article

Cite This Article

韩忠明, 孟怡新, 郭惠莹, 等. 基于动态异构网络的股价预测 [J]. 计算机应用研究, 2024, 41 (7): 2126-2133. (Han Zhongming, Meng Yixin, Guo Huiying, et al. Stock price prediction based on dynamic heterogeneous network [J]. Application Research of Computers, 2024, 41 (7): 2126-2133. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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