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Task-Oriented Snapshot Network Construction of Stock Market

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Intelligent Computing Theories and Application (ICIC 2021)

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Abstract

The stock market is a dynamic and complex system in which individual stocks interact with each other and thus influence the rules of the market as a whole. Moreover, we usually want to know how individual stocks and their interactions affect a particular economic indicator. In this paper, for a task, we use eXtreme Gradient Boosting and SHapley Additive exPlanations to construct snapshot networks of the stock market. The snapshot network gives a quantitative explanation of the target output at each moment in terms of the stocks themselves and their interactions. We take the stocks contained in Dow Jones Industrial Average (DJIA) as an example and DJIA itself as the task to construct the snapshot networks. The experimental results show that the snapshot networks can explain the tasks from three aspects: dynamic evolution, stocks themselves and their interactions.

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Acknowledgements

This research was funded by the National Natural Science Foundation of China, grant number 62066017.

Author information

Authors and Affiliations

  1. School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, 330013, China

    Jiancheng Sun, Huimin Niu & Si Chen

  2. Glasgow College, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Yunfan Hu

  3. School of Information Management, Jiangxi University of Finance and Economics, Nanchang, 330013, China

    Zhinan Wu

  4. School of Mathematics and Computer Science, Yichun University, Yichun, 336000, China

    Zhinan Wu

Authors
  1. Jiancheng Sun
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  2. Yunfan Hu
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  3. Zhinan Wu
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  4. Huimin Niu
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  5. Si Chen
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Corresponding author

Correspondence to Jiancheng Sun .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Shenzhen University, Shenzhen, China

    Jianqiang Li

  4. Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia

    Valeriya Gribova

  5. University of Wollongong, North Wollongong, NSW, Australia

    Prashan Premaratne

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Sun, J., Hu, Y., Wu, Z., Niu, H., Chen, S. (2021). Task-Oriented Snapshot Network Construction of Stock Market. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12838. Springer, Cham. https://doi.org/10.1007/978-3-030-84532-2_1

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  • DOI: https://doi.org/10.1007/978-3-030-84532-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-84531-5

  • Online ISBN: 978-3-030-84532-2

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