[Article] Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature

Research Article_s NLP
Thierry Warin , Aleksandar Stojkov


The application of Machine Learning Algorithms and unstructured data analysis have become a promising methodological advancement in the finance field. The paper’s central goal is to use a metadata-based systematic literature review to map current state of neural networks and machine learning in the finance field. By processing a large set of articles and its transformation into machine-readable data, we conduct a systematic review of the academic finance literature intersected with neural networks methodologies. The output is a data-driven meta-analysis of the two-decade evolution and the current state of academic inquieries into financial concepts and financial market trends.

Keywords: Efficient Market Hypothesis; Machine Learning; Network analysis; Sentiment analysis

Appendix of 5053 References Used in the Article