Prof. Yan JI

Award Citation

Algorithmic trading with advanced AI technologies has recently gained significant momentum, and its future progression seems inevitable. One of the most pressing concerns is the risk of AI-driven market manipulation, which benefits a small group of sophisticated speculators equipped with AI technologies while harming broader market participants by undermining competition, liquidity, and market efficiency. Through this project, Professor Ji and his collaborators will develop a comprehensive, data-driven quantitative framework, incorporating estimated synthetic trading environments from real market data and state-of-the-art reinforcement learning strengthened by deep learning techniques. Such a framework will enable quantitative assessments of how multiple self-interested AI-powered trading algorithms interact, leading to phenomena such as speculative bubbles, crashes, and collusion. The framework will also be used to quantitatively investigate regulatory policies aimed at countering AI-driven market manipulation.

Professor Ji is a financial economist whose research spans asset pricing, macro finance, and AI in finance. His research integrates insights and tools from industrial organization into theoretical models in asset pricing and capital market research. His prior work develops novel asset-pricing models that explicitly consider key organizational features of modern industries, highlighting the role of strategic competition among market leaders in determining industry dynamics and aggregate fluctuations. His latest work studies the implications of AI-powered trading for market efficiency, demonstrating the possibility of AI collusion in a financial market dominated by a few informed investors equipped with AI technologies.