Research

Research Interests

• Mathematical Finance, Market Microstructure, Equilibrium Models and Liquidity Risk
  
• Stochastic Analysis and Forward-backward Stochastic Differential Equations
  
• Machine Learning, Game Theory with Applications in Strategyproof Conference Review
  
• Dynamical Systems, Reinforcement Learning and Compressed Sensing with Applications in Big Data
  

Preprints

• A Dynamic Equilibrium Model of Liquidity Risk
  (with Agostino Capponi, and Johannes Muhle-Karbe)
  Submitted, 2025.
  
• Generative Market Equilibrium Models with Stable Adversarial Learning via Reinforcement Link
  (with Anastasis Kratsios, Qiang Sun, and Zhanhao Zhang)
  Submitted, 2025.
  
• Dynamic Portfolio Choice with Intertemporal Hedging and Transaction Costs
  (with Johannes Muhle-Karbe, and James Sefton)
  Submitted, 2024.
  

Publications

• The Price of Information
  (with Sebastian Jaimungal)
  SIAM Journal on Financial Mathematics, Vol. 15 (2024), No. 3, pp. SC54-SC67.
  
• Deep Learning Algorithms for Hedging with Frictions
  (with Daran Xu, and Zhanhao Zhang)
  Digital Finance, Vol. 5 (2023), pp. 113 - 147.
  
• An Equilibrium Model for the Cross-Section of Liquidity Premia
  (with Johannes Muhle-Karbe, and Chen Yang)
  Mathematics of Operations Research, Vol. 48 (2022), No. 3, pp. 1423 - 1453.
  
• Asset Pricing with General Transaction Costs: Theory and Numerics
  (with Lukas Gonon, and Johannes Muhle-Karbe)
  Mathematical Finance, Vol. 31 (2021), No. 2, pp. 595-648.
  
• On Strategyproof Conference Peer Review
  (with Yichong Xu, Han Zhao, and Nihar B. Shah)
  IJCAI 2019 (The 28th International Joint Conference on Artificial Intelligence).
  
• Sublinear Time Numerical Linear Algebra for Structured Matrices
  (with David P. Woodruff)
  AAAI 2019 (The 33th Association for the Advancement of Artificial Intelligence Conference).
  
• Improved Algorithms for Adaptive Compressed Sensing
  (with Vasileios Nakos, David P. Woodruff, and Hongyang Zhang)
  ICALP 2018 (The 45th International Colloquium on Automata, Languages and Programming).
  

Thesis