研資局研究學者計劃 | 教資會及研資局獎項

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

讚詞

近年來，基於先進人工智能技術的算法交易發展勢頭強勁。其中最緊迫的擔憂之一是人工智能驅動的市場操縱風險。這種風險使少數掌握人工智慧技術的精明投機者受益，同時損害更廣泛的市場參與者，破壞競爭、流動性和市場效率。通過該項目，吉教授及其合作者將開發一個全面的、數據驅動的量化框架，該框架融合了基於真實市場數據估算的合成交易環境，以及基於深度學習技術加持的強化學習。該框架將能夠定量評估多種自利的人工智能交易算法如何相互作用，從而導致投機泡沫、市場崩盤和市場共謀等現象。該框架還將用於定量研究旨在打擊人工智能驅動的市場操縱的監管政策。

吉教授的研究領域涵蓋資產定價、宏觀金融及金融領域的人工智能。他的研究將產業組織的洞見和工具融入資產定價和資本市場研究的理論模型中。他先前的研究開發的資產定價模型強調了市場領導者之間的戰略競爭在決定行業動態和總體波動方面的作用。他的最新研究探討了人工智能交易對市場效率的影響，揭示了在由少數掌握人工智能技術的知情投資者主導的金融市場中，由人工智能驅動的交易算法產生合謀的可能性。