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Price, Complexity, and Mathematical Model

Author

Listed:
  • Na Fu

    (Department of Management and Economics, Tianjin University, Tianjin 300072, China
    Tianjin Agricultural University, No. 22 Jinjing Road, Xiqing District, Tianjin 300392, China)

  • Liyan Geng

    (School of Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China)

  • Junhai Ma

    (Department of Management and Economics, Tianjin University, Tianjin 300072, China)

  • Xue Ding

    (Department of Management and Economics, Tianjin University, Tianjin 300072, China)

Abstract

The whole world has entered the era of the Vuca. Some traditional methods of problem analysis begin to fail. Complexity science is needed to study and solve problems from the perspective of complex systems. As a complex system full of volatility and uncertainty, price fluctuations have attracted wide attention from researchers. Therefore, through a literature review, this paper analyzes the research on complex theories on price prediction. The following conclusions are drawn: (1) The price forecast receives widespread attention year by year, and the number of published articles also shows a rapid rising trend. (2) The hybrid model can achieve higher prediction accuracy than the single model. (3) The complexity of models is increasing. In the future, the more complex methods will be applied to price forecast, including AI technologies such as LLM. (4) Crude-oil prices and stock prices will continue to be the focus of research, with carbon prices, gold prices, Bitcoin, and others becoming new research hotspots. The innovation of this research mainly includes the following three aspects: (1) The whole analysis of all the articles on price prediction using mathematical models in the past 10 years rather than the analysis of a single field such as oil price or stock price. (2) Classify the research methods of price forecasting in different fields, and found the common problems of price forecasting in different fields (including data processing methods and model selection, etc.), which provide references for different researchers to select price forecasting models. (3) Use VOSviewer to analyze the hot words appearing in recent years according to the timeline, find the research trend, and provide references for researchers to choose the future research direction.

Suggested Citation

  • Na Fu & Liyan Geng & Junhai Ma & Xue Ding, 2023. "Price, Complexity, and Mathematical Model," Mathematics, MDPI, vol. 11(13), pages 1-30, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2883-:d:1180658
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    References listed on IDEAS

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