Advanced graduate course for Ph.D. students interested in pursuing a professional/research career in financial engineering. The course will start with a quick review of 222: the basics of Brownian motion, martingales, Ito's calculus, risk-neutral pricing in continuous time models. It then covers rigorously and in depth the most fundamental probability concepts for financial engineers, including stochastic integral, stochastic differential equations, and semi-martingales. The second half of the course will discuss the most recent topics in financial engineering, such as credit risk and analysis, risk measures and portfolio optimization, and liquidity risk and models.

The objective of this course is to give a first approach to microstructure and to present some key issues in high frequency trading. Part one introduces the main notions in microstructure: how electronic markets work, limit order books mechanism, dark pools and auction markets. Students will learn through examples extracted from research articles. Part two of the course introduces reinforcement learning methods and Q-learning applied to optimal asset allocation, optimized trade execution and smart order routing.

NOTE: Class will be moving to TTH 12:30-2pm

Repeat Rules

Course is not repeatable for credit.