Global Quantitative Investment Regulatory Policy Analysis and Its Implications for China's Regulatory System

DOI: https://doi.org/10.62517/jike.202304221

Author(s)

Tianquan Liu, Xingyuan Li*

Affiliation(s)

College of Economics and Management, Hunan University of Arts and Science, Changde 415100, Hunan, China *Corresponding Author.

Abstract

In an era marked by globalization and frequent "black swan" events, this study examines the complexities and strategic opacity of quantitative investment, a key product of financial innovation, within the scope of global financial regulation. Utilizing detailed comparative analysis, it explores diverse regulatory approaches in major economies, including the United States, the European Union, and key Asian countries. The research highlights the U.S.'s focus on balancing market transparency with financial innovation, the EU's emphasis on market stability and systemic risk prevention, and the trend towards regulatory modernization and internationalization in Asia. This study underscores the dual role of quantitative investment in enhancing market efficiency and optimizing resource allocation, while acknowledging the associated systemic risks and regulatory challenges. Focusing on China, the research identifies the critical developmental stages in regulatory practices, emphasizing the need for technological adaptation and international cooperation. In conclusion, the paper proposes comprehensive recommendations for improving China's quantitative investment regulation. These aim to reinforce legal frameworks, advance regulatory technologies, intensify risk management, foster global collaboration, and augment investor education and protection. The suggestions are intended to guide China towards effective regulatory policies that harmonize financial safety with technological advancement, ensuring market stability and transparency.

Keywords

Quantitative Investment Regulation; Comparative Regulatory Analysis; Financial Market Innovation

References

[1] Chen, C., Zhang, P., Liu, Y., & Liu, J. (2020). Financial quantitative investment using convolutional neural network and deep learning technology. Neurocomputing, 390, 384-390. [2] Begenau, J., & Landvoigt, T. (2022). Financial regulation in a quantitative model of the modern banking system. The Review of Economic Studies, 89(4), 1748-1784. [3] Fang, Y., Chen, J., & Xue, Z. (2019). Research on quantitative investment strategies based on deep learning. Algorithms, 12 (2), 35. [4] Emerson, S., Kennedy, R., O'Shea, L., & O'Brien, J. (2019, May). Trends and applications of machine learning in quantitative finance. In 8th international conference on economics and finance research (ICEFR 2019). [5] Securities and Exchange Commission (SEC). (2018). Regulatory Actions in Quantitative Trading. [6] Dodd, C., & Frank, B. (2010). Dodd-Frank Wall Street Reform and Consumer Protection Act. [7] Pittman, E. L. (2016). Quantitative Investment Models, Errors, and the Federal Securities Laws. NYUJL & Bus., 13, 633. [8] European Commission. (2014). Markets in Financial Instruments Directive (MiFID II). [9] Escribá-Pérez, J., & Murgui-García, M. J. (2017). Do market regulations reduce investment? Evidence from European regions. Regional Studies, 51 (9), 1336-1347. [10] Monsreal-Barrera, M. M., Cruz-Mejia, O., Ozkul, S., & Saucedo-Martínez, J. A. (2020). An optimization model for investment in technology and government regulation. Wireless Networks, 26 (7), 4929-4941.