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Exploring Complexity: A Bibliometric Analysis of Agent-Based Modeling in Finance and Banking

Author

Listed:
  • Ștefan Ionescu

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

  • Camelia Delcea

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

  • Ionuț Nica

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

  • Gabriel Dumitrescu

    (Department of Accounting and Audit, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

  • Claudiu-Emanuel Simion

    (Doctoral School of Management, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

  • Liviu-Adrian Cotfas

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, 010552 Bucharest, Romania)

Abstract

This study conducts a comprehensive bibliometric analysis of the use of agent-based modeling (ABM) in finance and banking, aiming to uncover how this methodology has evolved over the past two decades. It addresses the following overarching question: How has ABM contributed to the development of financial research in terms of trends, key contributors, and thematic directions? The relevance of this topic is based on the growing complexity of financial systems and the limitations of traditional models in capturing dynamic interactions, contagion effects, and systemic risks. Using a refined dataset of 489 articles from the Web of Science (2000–2024), selected through a multi-step keyword and relevance screening process, we apply bibliometric techniques using R Studio (version 2024.12.1+563) and Bibliometrix (version 4.3.3). The analysis reveals stable publication growth, strong international collaborations (notably Italy, USA, and China), and core thematic areas such as risk management, market simulation, financial stability, and policy evaluation. The findings highlight both well-established and emerging research fronts, with agent-based models increasingly used to simulate real-world financial phenomena and support regulatory strategies. By mapping the intellectual structure of the field, this paper provides a solid foundation for future interdisciplinary research and practical insights for policymakers seeking innovative tools for financial supervision and decision making.

Suggested Citation

  • Ștefan Ionescu & Camelia Delcea & Ionuț Nica & Gabriel Dumitrescu & Claudiu-Emanuel Simion & Liviu-Adrian Cotfas, 2025. "Exploring Complexity: A Bibliometric Analysis of Agent-Based Modeling in Finance and Banking," IJFS, MDPI, vol. 13(2), pages 1-37, April.
    • Handle: RePEc:gam:jijfss:v:13:y:2025:i:2:p:65-:d:1634691
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    References listed on IDEAS

    as
    1. Robert L. Axtell & J. Doyne Farmer, 2025. "Agent-Based Modeling in Economics and Finance: Past, Present, and Future," Journal of Economic Literature, American Economic Association, vol. 63(1), pages 197-287, March.
    2. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2015. "Systemic Risk and Stability in Financial Networks," American Economic Review, American Economic Association, vol. 105(2), pages 564-608, February.
    3. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
    4. Juan E. Trinidad Segovia & Fabrizio Di Sciorio & Raffaele Mattera & Maria Spano & Wei Xing Zhou, 2022. "A Bibliometric Analysis on Agent-Based Models in Finance: Identification of Community Clusters and Future Research Trends," Complexity, Hindawi, vol. 2022, pages 1-11, September.
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