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Research on Dynamic Characteristics of Stock Market Based on Big Data Analysis

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  • Ping Yang
  • Xiaohong Hou
  • Gengxin Sun

Abstract

The stock market is a real and continuously evolving extremely complex dynamic system. This paper analyzes the change of stock market efficiency from the perspective of dynamic evolution, and the recursive graph method is used to obtain the dynamic characteristics of stock price time series. For the sharp rise and fall of stock prices, this paper uses the heuristic segmentation algorithm of nonlinear time series mutation detection to study the detection of market dynamics characteristics before the stock market crash. Based on the above research results, this paper studies the dynamic evolution of financial markets and the construction of a complex network of dynamic characteristics between financial markets. The simulation results show that there are typical characteristics of small world network in stock market complex network, the stock market complex network shows stronger synchronization ability, and the transmission range of information between the stock markets in the complex network is significantly expanded.

Suggested Citation

  • Ping Yang & Xiaohong Hou & Gengxin Sun, 2022. "Research on Dynamic Characteristics of Stock Market Based on Big Data Analysis," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-8, March.
    • Handle: RePEc:hin:jnddns:8758976
    DOI: 10.1155/2022/8758976
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    Cited by:

    1. Mengrui Zhu & Hua Xu & Xingyu Gao & Minggang Wang & André L. M. Vilela & Lixin Tian, 2022. "Identification of Breakpoints in Carbon Market Based on Probability Density Recurrence Network," Energies, MDPI, vol. 15(15), pages 1-18, July.

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