Regular biography
Hans Buehler is a Research Fellow in the Department of Mathematical Institute at the University of Oxford. His research interests include Stochastic Analysis, Theoretical Mathematical Finance, Machine Learning in Finance, Derivative Market Modelling, and Risk Management. He is associated with research groups in Mathematical and Computational Finance and Machine Learning and Data Science. Buehler has contributed to various publications and patents, including work on Deep Hedging, Multi-Asset Market Simulation, and Statistical Hedging. He is also recognized with the Risk Quant of the Year 2022 award.
Scholar-generated biography
Hans Buehler is a researcher at the University of Oxford, specializing in AI and Quantitative Finance. His work focuses on developing advanced methodologies for financial markets, including hedging strategies, volatility modeling, and market simulation. Buehler's research integrates machine learning techniques, particularly reinforcement learning, to address challenges in derivative pricing and risk management. He has published extensively on topics such as deep hedging, consistent variance curve models, and stochastic volatility. His contributions emphasize the application of AI to financial problems, aiming to improve market efficiency and robustness under various market frictions.