Three decennaries of artificial neural networks in finance: a bibliometric review and future research agenda

Amit Kumar and Manpreet Kaur

International Journal of Indian Culture and Business Management, 2025, vol. 34, issue 1, 1-26

Abstract: Artificial neural networks (ANNs) have revolutionised financial operations due to their abilities to learn from nonlinear and unstructured financial data. The current study aims to systematically map the conceptual and intellectual structure of research on ANNs in the finance domain based on bibliometric analysis and network visualisation of 3,106 articles published during the period 1992 to 2022. The study identifies the research trends, major contributors, and scientific collaborations in the field. Bibliographic coupling analysis and co-citation analysis of the documents revealed five clusters and three clusters of documents, respectively. Additionally, the current study intensively reviewed the important studies lying in each cluster to provide a comprehensive assessment of the relevant literature, thereby uncovered the knowledge gaps and challenges, and provided recommendations for future studies. Therefore, the study can be taken as a baseline by future researchers and financial practitioners to advance in the concerned field with the appropriate approach.

Keywords: neural networks; bibliometric; finance; forecasting; network analysis; research trends. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijicbm:v:34:y:2025:i:1:p:1-26

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