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Exploring the financial indicators to improve the pattern recognition of economic data based on machine learning

  • S.I. : DPTA Conference 2019
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Various economic data in the financial market need to be pattern-recognized to improve the efficiency of economic data pattern recognition, further improve the accuracy of economic-related decisions, and promote stable economic development. Based on machine learning technology, this study establishes a statistical model by establishing a multiple regression model to extract financial indicators that have significant effects on the financing trade of listed companies. Moreover, this study provides a preliminary empirical model for judging whether a company conducts financing trade based on some company’s financial indicators and uses data to verify the consistency of the model. In addition, this study conducts research and demonstration of the algorithm model of this research through empirical research. The research results show that the model shows high reliability and validity in accurately identifying whether the enterprise has the characteristics of conducting financing trade.

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Acknowledgements

This paper was supported by Key projects of Philosophy and Social Sciences Research, Ministry of Education of China: Cultivating New Advantages of China’s International Competition, Studying the Strategic Path of Building a Strong Trade Country (Grant No. 16JZD018), General Program of Natural Science Foundation of Guangdong Province of China: The Influence Mechanism and Empirical Test of the Heterogeneity of Labor Force in Host Country on China’s Industrial Transfer to Africa and High-level University Research Projects, Major Base Projects: Theoretical and Policy Research on Improving the Quality of China’s Foreign Trade Development under the Background of Sino-US Trade Friction (Grant No. 18JD05).

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Authors and Affiliations

  1. Research Center for International Trade and Economics, Institute for African Studies, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Xiaohui Wei

  2. Research Center for International Trade and Economics, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Wanling Chen

  3. Postdoctoral Station of Peking University, Beijing, 100871, China

    Xiao Li

  4. Postdoctoral Station of China Development Bank, Beijing, 100032, China

    Xiao Li

  5. Research Institute of China Development Bank, Beijing, 100032, China

    Xiao Li

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  1. Xiaohui Wei
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  2. Wanling Chen
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  3. Xiao Li
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Correspondence to Wanling Chen.

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Wei, X., Chen, W. & Li, X. Exploring the financial indicators to improve the pattern recognition of economic data based on machine learning. Neural Comput & Applic 33, 723–737 (2021). https://doi.org/10.1007/s00521-020-05094-0

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