Statistical Arbitrage

This two day workshop introduces delegates to statistical arbitrage strategies, including pairs trading, with particular reference to research, testing and implementation. Relevant software (EXCEL) will be used throughout the workshop to illustrate examples and to help students practice the essential steps in developing a stat arb strategy.

March 29 to March 30, 2017
Duration: Two days (9.00am to 5.00pm)
Location: The Tower Hotel – London, UK
Trainer: Christian Schaller
Course fee: £1890 + VAT – Register online

Course Outline


+ The different types of statistical arbitrage strategies
+ Stationarity, cointegration, mean reversion, and momentum

Required tools in EXCEL

+ The pros and cons of using EXCEL
+ Quick survey of required functions
+ Writing custom add-in functions using VBA
+ Exercises: building some useful utilities for trading research

Directional Trading

+ Concept of stationarity, and why it is useful
+ Statistical test for stationarity
+ Exercise: Testing for stationarity
+ Testing for mean-reversion: half-life based on Ornstein-Uhlenbeck formula
+ Why is computing half-life better than computing average holding period?
+ Exercise: Computing the half-life of mean-reversion

Pairs and Triplets Trading

+ Pairs and triplets trading
+ Concept of cointegration and why it is useful
+ How is cointegration different from correlation?
+ Statistical tests for cointegration
+ Exercise: Find out if GLD-GDX is cointegrating
+ Finding the best hedge ratio
+ Trading cointegrated triplets
+ What are the best markets to pairs trade?

Stop Losses, Profit Targets, and Dynamic Scaling

+ When do stop losses stop losses?
+ Setting optimal profit targets
+ The purpose of dynamic scaling
+ Using simulation to assess stops, targets, and scaling policies

Managing a Portfolio of Mean-Reverting Trades

+ Formulating a well-posed problem in financial economics
+ Formulating a well-posed mathematical problem
+ Solving well-posed investment problems
+ Implementing solutions in practice
+ Incorporating risk management