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Using Big Data to Discover Chaos in China’s Futures Market During COVID-19

Lin Tie1, Bin Huang1, Bin Pan1, Guang Sun1,2,*
1 Hunan University of Finance and Economics, Changsha, 410205, China
2 University of Alabama, Tuscaloosa, AL 35487, USA
* Corresponding Author: Guang Sun. Email:

Computers, Materials & Continua 2021, 69(3), 3095-3107. https://doi.org/10.32604/cmc.2021.019363

Received 11 April 2021; Accepted 27 May 2021; Issue published 24 August 2021

Abstract

COVID-19 was first reported in China and quickly spread throughout the world. Weak investor confidence in government efforts to control the pandemic seriously affected global financial markets. This study investigated chaos in China’s futures market during COVID-19, focusing on the degree of chaos at different periods during the pandemic. We constructed a phase diagram to observe the attractor trajectory of index futures (IFs). During the COVID-19 outbreak, overall chaos in China’s futures market was increasing, and there was a clear correlation between market volatility and the macroenvironment (mainly government regulation). The Hurst index, calculated by rescaled range (R/S) analysis, was 0.46. The price and return of IFs showed long-term correlation and fractal characteristics; the relevant dimensions of the futures market were 2.17. Overall, under the influence of an emergency (COVID-19), chaos in China’s financial market intensified, creating a need for timely government intervention and macrocontrol of the market. This study’s findings can help improve the government’s understanding of the phenomenon of financial chaos caused by emergencies. This study also provides theoretical guidance for controlling financial chaos and maintaining healthy economic development when faced with similar events in the future.

Keywords

Chinese futures market; COVID-19; chaos; Lyapunov index; Hurst index

Cite This Article

L. Tie, B. Huang, B. Pan and G. Sun, "Using big data to discover chaos in china’s futures market during covid-19," Computers, Materials & Continua, vol. 69, no.3, pp. 3095–3107, 2021.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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