Financial Market Forecasting with Artificial Neural Networks: A Bibliometric Analysis and Future Research Direction Kumar Amit1,*, Kaur Manpreet2, Mittal Anil Kumar3 1Research Scholar, University School of Management, Kurukshetra University, Kurukshetra, Haryana, India, (E-mail: amit98in@gmail.com) 2Research Scholar, University School of Management, Kurukshetra University, Kurukshetra, Haryana, India, (E-mail: manpreetkaur27oct@gmail.com) 3Professor, University School of Management, Kurukshetra University, Kurukshetra, Haryana, India, (E-mail: anilmittalkuk@gmail.com) *Corresponding author E-mail: amit98in@gmail.com
Online Published on 02 February, 2024. Abstract Artificial neural networks (ANNs) have revolutionized financial market forecasting by yielding high precision in predictive results owing to their abilities to learn from a complex set of non-linear and unstructured financial data. The current study is a novel work that attempts to systematically investigate the existing literature on employing ANNs for financial market forecasting through a bibliometric analysis of 235 articles and a keyword-based content analysis of influential studies published during the past two decades (2002-2022). The study contributes to the extant body of knowledge through unveiling research trends, prominent contributors, research collaborations, and prominent and emerging research areas in the concerned domain. Furthermore, the study uncovered challenges in designing and implementing ANNs, and recommended feasible solutions, also. Thus, the results of the current study can be taken as reference points by novice researchers and various financial market practitioners to direct their endeavours and advance in this field. Top Keywords Neural Networks, Financial Markets, Forecasting, Bibliometric. Top |