Machine Learning Algorithm Applications in Empirical Finance: A Review of the Empirical Literature

Xiaochuan Liao ()
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Xiaochuan Liao: University of Birmingham, School of Computer Science

A chapter in Proceedings of the 3rd International Conference on Economic Development and Business Culture (ICEDBC 2023), 2024, pp 311-316 from Springer

Abstract: Abstract The modern finance industry has many challenges to handle, so advanced tools are applied to assist people in trying to find a solution to those complex problems. Machine learning is a powerful tool that can help researchers tackle difficult issues, including those in the financial industry. In this paper, I reviewed literature focusing on machine learning algorithm applications in empirical finance. I divide the literature review into three sub-sectors: financial market prediction, bankruptcy prediction and credit risk analysis, and other notable aspects. It is found that researchers widely use algorithms like support vector machines and neural networks. Finally, based on my review of the literature, I provide my insights in this area.

Keywords: machine learning; financial market prediction; bankruptcy prediction; literature review (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-246-0_38

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DOI: 10.2991/978-94-6463-246-0_38

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