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Intelligent Finance: Emerging Applications and Challenges of Machine Learning in Asset Pricing
- 1 Hefei University of Technology, Hefei City, Anhui Province, 230000, China
* Author to whom correspondence should be addressed.
Abstract
This paper explores in depth the impact of big data and machine learning on asset pricing. By addressing the limitations of traditional asset pricing models, it analyzes the challenges and opportunities brought by big data to the financial markets. Traditional models, due to their linear assumptions, struggle to handle the complexity of high-dimensional data. However, machine learning techniques, particularly deep learning, overcome this issue with their powerful data processing capabilities, thereby enhancing the model’s external validation capacity. This paper summarizes various methods of applying modern machine learning in asset pricing, including feature engineering and end-to-end deep learning, and discusses the adaptive mechanisms of AI technologies to the complexity of asset pricing. Through case analysis, the article also emphasizes the significant effects of AI in improving predictive accuracy and market efficiency. This paper provides a new perspective for asset pricing research and offers practical pathways for the intelligence and dynamic adaptability of financial markets.
Keywords
Asset pricing, Machine learning, Artificial intelligence, Big data
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Cite this article
Jiang,Y. (2025). Intelligent Finance: Emerging Applications and Challenges of Machine Learning in Asset Pricing. Advances in Economics, Management and Political Sciences,156,11-20.
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