| Issue |
SHS Web Conf.
Volume 218, 2025
2025 2nd International Conference on Development of Digital Economy (ICDDE 2025)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 9 | |
| Section | Digital Finance: Innovation, Regulation, and Inclusion | |
| DOI | https://doi.org/10.1051/shsconf/202521801003 | |
| Published online | 03 July 2025 | |
Artificial intelligence and big data assist investment
1 School of Business, Xiangtan University, 411105, Xiangtan, China
2 School of economics, Jinan University, 510632, Guangzhou, China
3 School of economics, Pearl River College, Tianjin University of Finance and Economics, 301800, Tianjin, China
* Corresponding author: AndreaTeng12138@outlook.com
Excessive stock market volatility amplifies financial risks, necessitating AI-driven decision-support systems for risk mitigation. Integrating AI and big data analytics enables real-time market monitoring and actionable insights for investors and regulators, enhancing global financial profitability through improved forecasting and risk management. This study combines game theory principles with AI technologies to develop market stabilization strategies, simulating multi-agent interactions to optimize trading rules and regulatory frameworks. Through price game modeling, it examines price dynamics and investor strategy equilibria across time horizons, highlighting AI’s dual role in predicting volatility and balancing short-term gains with long-term stability. While addressing stakeholder conflicts, the research acknowledges AI’s complex challenges alongside its transformative potential. The findings offer practical guidance for leveraging AI’s benefits in finance while managing risks, contributing to sustainable economic growth through enhanced understanding of intelligent systems’ operational mechanisms.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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