Regulations of High-Frequency Quantitative Trading in the Era of Artificial Intelligence

Quantitative trading firms complete short-term speculative trading through their high-frequency arbitrage transactions, shifting from company information analysis to market liquidity analysis. They can make profits in short-term zero-sum games without relying on company financial analysis, achieving a transition from “financialized” approaches to “AI-driven” methodologies. Although artificial intelligence has endowed quantitative trading with new strategies, granting it a disproportionate lead over human traders in short-term market competition, it runs counter to technological humanism and affects the stability of the securities market. To achieve the healthy development of the securities market and fair competition among investors, the regulatory logic of the securities market in the era of artificial intelligence should shift from information disclosure to trading structure, and a regulatory system for new risks of quantitative trading should be improved. The transparency of algorithms should be enhanced, high-frequency trading should be appropriately restricted, and dynamic responsive regulations that go beyond the technological neutrality of algorithms should be adopted. Market-acquisitive quantitative trading should be identified as market manipulation behavior and punished in accordance with the Securities Law.