Bo Hu

Bo Hu is an assistant professor of finance at George Mason University, where he teaches managerial finance, fixed income, and international finance in MBA and MSF programs at the Costello College of Business.

Bo has published research articles in top journals such as Management Science, Operations Research, and Journal of Financial and Quantitative Analysis (forthcoming). Drawing on financial economics, machine learning, and statistical physics, he studies the evolving function of financial markets in an era increasingly shaped by algorithms, big data, and artificial intelligence. Much of his work addresses questions of broad relevance and significant policy importance, including how algorithmic trading affects market stability, how position limits influence commodity markets, and how new technologies reshape price efficiency and investors’ information processing.

Bo has presented his research at leading international finance conferences (including WFA, EFA, SFS Cavalcade, CICF, NYU Stern Microstructure) and at major regulatory institutions such as the U.S. Securities and Exchange Commission (SEC) and the Bank for International Settlements (BIS). His strong interdisciplinary foundation, including extensive experience as a theoretical physicist on NSF- and NIH-funded projects, uniquely positions him to tackle some of the most challenging and consequential problems facing modern financial markets.

Education

• PhD in Finance, University of Maryland, 2019
• PhD in Physics, University of California San Diego, 2011
• BS in  Physics, University of Science and Technology of China, 2005 

Professional Designation 

• CFA Charterholder 

Interests

• Research: Asset Pricing, Market Microstructure, Machine Learning and AI
• Teaching: Investments, International Finance, Fixed-Income Securities 

Publications and Working Papers

Bo’s scholarly papers can be accessed here.

• “Whence LASSO? A Rational Interpretation” 
  with Wen Chen and Liyan Yang   
  Management Science, 2025 Special Issue on AI for Finance and Business Decisions 
  *Presented at WFA, EFA (European), CICF, AI and Big Data in Accounting and Finance Conference, CFEA Special Session on Machine Learning in Finance.
• “Dynamic Duopolistic Competition with Sticky Prices”  
  with Steven L. Heston 
  Operations Research, 2025 
• “How does Benchmarking Affect Market Efficiency? The Role of Learning Technology”
  with Wen Chen and Yajun Wang
  Journal of Financial and Quantitative Analysis, 2nd Revise & Resubmit 
  *Presented at EFA, MFA, CICF.  
• “Seeing is Believing: Annual Report Visuals and Stock Returns”   
  with Wesley Deng, Lei Gao, and Guofu ZHou 
  *Presented at EFA (European), SFS Cavalcada (Asia-Pacific), AI in Finance, Bretton-Woods Accounting & Finance Conference, CICF, Australasian Finance & Banking Conference. 
• “Algorithmic Arbitrage with Fat Tails”  
  with Wen Chen and Liyan Yang 
  *Presented at NYU Stern Microstructure Meeting and the 4th PKU-NUS Annual International Conference on Quantitative Finance & Economics. 
• “Limits to Leverage in Frictionless General Equilibrium”    
  with Albert S. Kyle 
• “Will Human Creatives Survive Generative AI Shocks?” 
  with Jiasun Li
  *Presented at UVA (Darden), Federal Reserve Bank of Cleveland, Wharton Business and Generative AI Conference, Tsinghua PBCSF; scheduled at GWU, CICF, Asia Meeting of Econometric Society, 5th Annual Hong Kong Conference on FinTech and AI in Finance.
• “Magnet Effect of Position Limits”
  with Wen Chen and Yajun Wang
• “Do Position Limits on Futures Trading Benefit Commodity Markets?”   
  with Wen Chen and Yajun Wang 
• “What if the Long Forward Rate is Flat?” 
• “On the  Puzzle of Bond Pricing in Cox-Ingersoll-Ross Model” 
• “Informed Trading and Internal Capital Markets: An Information-Theoretic Perspective"