COURSES: INTRODUCTION TO ALGORITHMIC TRADING STRATEGIES 2011-2013

Note: this course is superseded by the CQI introductory course Introduction to Quantitative Investment

Course Description

This course introduces students to quantitative trading. A trader usually starts with an intuition or a vague trading idea. Using mathematics, s/he turns the intuition into a quantitative trading model for analysis, back testing and refinement. When the quantitative trading model proves to be likely profitable after passing rigorous statistical tests, the trader implements the model on a computer system for automatic execution. In short, quantitative trading is the process where ideas are turned into mathematical models and then coded into computer programs for systematic trading. It is a science where mathematics and computer science meet. In this course, students study trading strategies from the popular academic literature and learn the fundamental mathematics and IT aspects of this emerging field. By working on the class projects, they will gain hands-on experience. After satisfactorily completing this course, the students will have the necessary quantitative, computing, and programming skills in quantitative trading. They are therefore well prepared for a front office role in hedge funds or banks.

Course Outline

Session
Topics
Readings
Homeworks
1
Overview of Algorithmic Trading
Lecturer handout
hw1
2
Hidden Markov Trading Model
Lecturer handout
hw2
lab
programming a hidden Markov chain
3
Pairs Trading by Cointegration
Lecturer handout
hw3
lab
programming a cointegration model; parameter sensitivity analysis
4
Optimal Pairs Trading by Stochastic Control
Lecturer handout
hw4
5
Pairs Trading by Stochastic Spread Methods
Lecturer handout
lab
programming a Kalman filter; parameter calibration
6
Technical Analysis: Linear Trading Rules
Lecturer handout
7
Portfolio Optimization
Lecturer handout
hw5
lab
strategy & portfolio optimization
8
Risk Management
Lecturer handout