研资局研究学者计划 | 教资会及研资局奖项

Biography
(只提供英文版)

Liwei Huang Associate Professor of Business in Department of Finance at The Hong Kong University of Science and Technology
Research interests include asset pricing, and its connections to industrial organization; imperfect competition; Macro finance; artificial intelligence (AI) in finance
RFS project — to 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.
Awards and Honours:
- RGC Research Fellow (2025)
- Marshall Blume Prize in Financial Research, 2017 and 2024, Rodney L. White Center at Wharton
- NSFC Excellent Young Scientists Fund (HK and Macau), 2024-2026
- Jacob Gold & Associates Best Paper Prize, 2024, ASU Sonoran Winter Finance Conference
- AAII Award for Outstanding Paper on Investments, 2020, Midwest Finance Association

Project Title
(只提供英文版)

AI-Powered Imperfect Competition in Financial Markets

赞词

近年来，基于先进人工智能技术的算法交易发展势头强劲。其中最紧迫的担忧之一是人工智能驱动的市场操纵风险。这种风险使少数掌握人工智慧技术的精明投机者受益，同时损害更广泛的市场参与者，破坏竞争、流动性和市场效率。通过该项目，吉教授及其合作者将开发一个全面的、数据驱动的量化框架，该框架融合了基于真实市场数据估算的合成交易环境，以及基于深度学习技术加持的强化学习。该框架将能够定量评估多种自利的人工智能交易算法如何相互作用，从而导致投机泡沫、市场崩盘和市场共谋等现象。该框架还将用于定量研究旨在打击人工智慧能驱动的市场操纵的监管政策。

吉教授的研究领域涵盖资产定价、宏观金融及金融领域的人工智能。他的研究将产业组织的洞见和工具融入资产定价和资本市场研究的理论模型中。他先前的研究开发的资产定价模型强调了市场领导者之间的战略竞争在决定行业动态和总体波动方面的作用。他的最新研究探讨了人工智能交易对市场效率的影响，揭示了在由少数掌握人工智能技术的知情投资者主导的金融市场中，由人工智能驱动的交易算法产生合谋的可能性。