A Review of Bilateral Matching Theory and Its Applications in Financial Markets

Huige Sun

doi:10.54254/2754-1169/2025.GL28986

Advances in Economics, Management and Political SciencesOpen access

A Review of Bilateral Matching Theory and Its Applications in Financial Markets

Research Article

Open Access

A Review of Bilateral Matching Theory and Its Applications in Financial Markets

Huige Sun ^1*

¹ NO2. Middle School Of Yantai Shandong

^*Corresponding author: 2657353883@qq.com

Published on 5 November 2025

AEMPS Vol.236

ISSN (Print): 2754-1177

ISSN (Online): 2754-1169

ISBN (Print): 978-1-80590-505-9

ISBN (Online): 978-1-80590-506-6

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Abstract

In modern financial markets, the matching efficiency among market participants is crucial to market stability and efficiency. Bilateral matching theory, as an important theoretical framework, provides scientific methods and tools for solving complex matching problems. This article aims to systematically review the development process of the bilateral matching theory, analyze its current application and challenges in the financial market, and explore future research directions. Through a comprehensive literature review, this study finds that although the bilateral matching theory has been widely applied in financial fields such as venture capital, bank loans, and the securities market, it still faces major challenges in practice, such as data privacy, model adaptability, and regulatory constraints. Research shows that the application of big data analysis, artificial intelligence and international cooperation can enhance the application efficiency of this theory, thereby strengthening market efficiency and competitiveness. Future research should focus on overcoming these challenges to fully unleash the potential of bilateral matching theory in financial markets.

Keywords:

Bilateral Matching Theory, Financial Markets, Matching Efficiency, Big Data, Artificial Intelligence

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References

[1]. Li, B., & Xu, Z. (2025). Probabilistic Linguistic Two-Sided Matching Decision-Making Methods and Applications (Vol. 436). Springer Nature.

[2]. Adachi, D., Son, S. J., & Yamaguchi, S. (2025). Monopsony in a Two-Sided Matching Market.

[3]. Kang Guangdi & Zhang Shuai. (2018). Historical Evolution and Domestic and International Application Research of Bilateral Matching Decision Theory. China Collective Economy, 31(2).

[4]. Nipkow, T. (2025). Gale-Shapley Algorithm.

[5]. Vaillant, Y., Vendrell‐Herrero, F., Bustinza, O. F., & Xing, Y. (2025). HRM algorithms: moderating the relationship between chaotic markets and strategic renewal. British Journal of Management, 36(2), 529-545.

[6]. Almohamad, H. A., & Duffuaa, S. O. (2002). A linear programming approach for the weighted graph matching problem. IEEE Transactions on pattern analysis and machine intelligence, 15(5), 522-525.

[7]. Zhu, X. (2020, July). Two-Sided Matching Venture Capital Model Based on Synthetic Effect. In LISS2019: Proceedings of the 9th International Conference on Logistics, Informatics and Service Sciences (pp. 595-605). Singapore: Springer Singapore.

[8]. Wen Sheng. (2006). Bilateral Matching Theory and Its Application in China's Banking Credit Market. Huazhong University of Science and Technology.

[9]. Zhang Jijun. (2011). A Study on the Matching of Small Banks' Credit Support for Small and Medium-sized Enterprises. Financial Theory and Teaching, (6), 3.

[10]. Zhang Shuhui, Li Yuanyuan, & Kong Yuqi. (2023). The Impact of Underwriter-Issuer Bilateral Matching Decisions on IPO Price Suppression. Journal of South China University: Social Sciences Edition (24)(4), 73-85.

References

[1]. Li, B., & Xu, Z. (2025). Probabilistic Linguistic Two-Sided Matching Decision-Making Methods and Applications (Vol. 436). Springer Nature.

[2]. Adachi, D., Son, S. J., & Yamaguchi, S. (2025). Monopsony in a Two-Sided Matching Market.

[3]. Kang Guangdi & Zhang Shuai. (2018). Historical Evolution and Domestic and International Application Research of Bilateral Matching Decision Theory. China Collective Economy, 31(2).

[4]. Nipkow, T. (2025). Gale-Shapley Algorithm.

[6]. Almohamad, H. A., & Duffuaa, S. O. (2002). A linear programming approach for the weighted graph matching problem. IEEE Transactions on pattern analysis and machine intelligence, 15(5), 522-525.

[8]. Wen Sheng. (2006). Bilateral Matching Theory and Its Application in China's Banking Credit Market. Huazhong University of Science and Technology.

[9]. Zhang Jijun. (2011). A Study on the Matching of Small Banks' Credit Support for Small and Medium-sized Enterprises. Financial Theory and Teaching, (6), 3.

Cite this article

Sun,H. (2025). A Review of Bilateral Matching Theory and Its Applications in Financial Markets. Advances in Economics, Management and Political Sciences,236,1-7.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICFTBA 2025 Symposium: Financial Framework's Role in Economics and Management of Human-Centered Development

ISBN: 978-1-80590-505-9(Print) / 978-1-80590-506-6(Online)

Editor: Lukáš Vartiak, Habil. Florian Marcel Nuţă

Conference website: https://2025.icftba.org/Galati.html

Conference date: 17 October 2025

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.236

ISSN: 2754-1169(Print) / 2754-1177(Online)

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