Artificial Intelligence in Economic Applications: Stock Trading, Market Analysis, and Risk Management

Yinlei Chen

doi:10.70393/6a6574626d.333232

Authors

Yinlei Chen Kyungil University

DOI:

https://doi.org/10.70393/6a6574626d.333232

ARK:

https://n2t.net/ark:/40704/JETBM.v2n5a02

Disciplines:

Finance

Subjects:

Investment Banking

References:

26

Keywords:

Internet of Things, Artificial Intelligence, Economy, Machine Learning, Stock Market, Neural Network

Abstract

Artificial Intelligence has become a fundamental driver of innovation in economic systems. This article provides an overview of its applications in stock trading, market analysis, and risk management. A systematic review of recent studies identifies the most widely used methods such as neural networks, deep learning, reinforcement learning, and hybrid approaches. This paper examines AI applications in economics, including stock trading, market analysis,

and risk assessment. A comprehensive taxonomy is proposed to investigate AI applications in various scopes of the proposed categories. Furthermore, real-world cases illustrate the practical deployment of artificial intelligence in financial institutions and enterprises. The findings suggest that artificial intelligence is a transformative force in the economy but challenges such as data quality, transparency, and regulatory adaptation remain open for future research.

Author Biography

Yinlei Chen, Kyungil University

Kyungil University, 38428, Republic of Korea.

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