STA 4505 – Algorithmic Trading


If you are interested in taking this course, please read through chapters 1-4 of Shreve’s book on Stochastic Calculus for finance volume 2. Spend more time on chapters 3 and 4, with a light reading of chapters 1 and 2.

The video lectures 7, 8 and 9 from STA 2502 may also be helpful.

The course is open for auditing, however, if you are currently not enrolled as a student at the University of Toronto, there is an auditing fee. Email me for more information.

Course Overview

With the availability of high frequency financial data, new areas of research in stochastic modeling and stochastic control have opened up. This 6 week course will introduce students to the basic concepts, questions and methods that arise in this domain. We will begin with the classical market microstructure models, understand different theories of price formation and price discovery, identify different types of market participants, and then move on to reduced form models. Next, we will investigate some of the typical algorithmic trading strategies employed in industry for different asset classes. Finally, we will develop stochastic optimal control problems for solving optimal liquidation and high frequency market making problems and demonstrate how to solve those problems using the principles of dynamic programming leading to Hamilton-Jacobi-Bellman equations. Students will also have a chance to work with historical limit order book data, develop Monte Carlo simulations and gain a working knowledge of the models and methods. Tentative topics include
– Limit Order Books
– Overview of Stochastic Calculus
– Stochastic Control & Dynamic Programming
– Optimal Execution
– Market Making
– Statistical Arbitrage
– Classification
– Reinforcement Learning


This short course is based off of my book Algorithmic and High-Frequency Trading.

Algorithmic and High Frequency Trading,

with Álvaro Cartea and Jose Penalva,

Cambridge University Press, now available!

Order here from CUPOrder here from

Click here for the book website where you can find data, code and other materials related to the book.