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.
You may also be interested in the Research-in-Options minicourse on machine learning and algorithmic trading.
Course Time and Location
First class Jan 9, 2018
Makeup class (repeat of lec 1) Jan 15, 2018 (Stewart 409, 6 pm – 9 pm)
2nd class Jan 30, 2018 (Stewart 409, 6 pm – 9 pm)
Tuesday’s (adhoc) 6pm – 9pm,
Stewart Building, room 409
149 College Street
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 by looking at several features seen in intra-day financial data, and examine how to build simple machine learning based models to describe the behaviour of the data. Next, we will investigate some of the typical algorithmic trading strategies employed in industry ranging from Bollinger bands, momentum and mean-reversion strategies, pairs trading, and statistical arbitrage. We will then develop stochastic optimal control problems for algorithmic trading and show how to solve them using the principles of dynamic programming leading to Hamilton-Jacobi-Bellman equations. Finally, we will look at reinforcement learning approaches to algorithmic trading. 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
– Hidden Markov Models
– Functional Principal Component Analysis
– Reinforcement Learning
This short course is based off of my book Algorithmic and High-Frequency Trading.
|Algorithmic and High Frequency Trading,
Cambridge University Press, now available!
Click here for the book website where you can find data, code and other materials related to the book.
Jupyter Notebooks < click