The Mathematical and Statistical Finance group focuses on research in quantitative modeling of financial markets across a broad spectrum of topics. Particular areas of focus include statistical arbitrage, market microstructure and high-frequency modeling, optimal execution, analysis and modeling of limit order books, machine learning and empirical asset pricing, portfolio construction, financial econometrics, decentralized finance, and synthetic data generation. The research agenda is driven by a wide spectrum of mathematical tools from probability, statistics, stochastic analysis, partial differential equations, machine learning, econometrics and time series analysis, network science, optimization, and simulations.