Fortune: AI and High-Frequency Trading

This article provides a comprehensive overview of the development of algorithmic trading, tracing its evolution from simple program trading in the 1980s to today's sophisticated high-frequency trading (HFT) and emerging AI-powered trading systems. The author, with 14 years of research experience, critically examines both the advantages and significant risks associated with AI-driven financial technologies, drawing on historical examples like the Black Monday crash and the 2010 flash crash to illustrate potential systemic vulnerabilities. The key contribution is a nuanced exploration of how AI trading technologies can simultaneously offer remarkable efficiency and pose substantial risks to market stability. The research highlights critical concerns such as algorithmic herding, potential amplification of market biases, and the risk of multiple trading algorithms making simultaneous decisions that could trigger significant market disruptions. While acknowledging the computational advantages of AI over human traders, the author emphasizes the need for careful implementation and robust regulatory oversight to prevent potential market failures.