Practitioner course in statistical arbitrage
Pairs Trading and Mean Reversion
The pairs trade from selection to testing: how to find candidate pairs, the distance and cointegration methods, hedge ratios, spread z-scores, trading rules, and the reasons pairs stop working.
Pairs trading is the simplest market-neutral strategy and the usual starting point for statistical arbitrage. Two related instruments, a long position in one and a short position in the other, and a rule for when the gap between them is wide enough to trade. The idea fits in a sentence; doing it carefully takes a course.
How do you choose a pair to trade?
Start from an economic reason the two prices should move together, such as two companies in the same business or two share classes of one firm. Then test whether the spread between them is stable. Searching thousands of pairs for the best statistical fit finds pairs that fitted the past by chance, so the course treats pair selection as a multiple-testing problem.
When should you enter and exit a pairs trade?
A common rule is to enter when the spread is two standard deviations from its mean and exit when it returns to the mean. The right thresholds depend on how fast the spread reverts, its half-life, and on costs. You will estimate both and test the rules out of sample rather than picking thresholds that looked best in the sample.
Who is this course for?
Traders and analysts learning market-neutral strategies, and students preparing for Statistical Arbitrage and Cointegration Models for Spread Trading. It counts toward the Certificate in Statistical Arbitrage.
What you will be able to do
- Screen a universe for candidate pairs and explain the risk of data snooping.
- Apply the distance method and the cointegration method and compare them.
- Estimate hedge ratios, including rolling and Kalman filter estimates.
- Set entry, exit and stop rules for a spread and test them out of sample.
- Identify when a pair relationship has broken.
Syllabus, module by module
The pairs trade
Origins, the logic of relative value, and what a pair has to have in common.
Finding pairs
Economic links, correlation screens and the multiple-testing problem of searching many pairs.
The distance method
Normalised prices, sum of squared differences and the Gatev, Goetzmann and Rouwenhorst study.
The cointegration method
Engle-Granger tests, hedge ratios and the half-life of the spread.
Dynamic hedge ratios
Rolling regression and the Kalman filter for relationships that drift.
Trading rules
Z-score entries and exits, time stops, and sizing a book of pairs.
When pairs break
Corporate events, regime change and tests for a structural break.
Project lab
Supervised work on the assessed pairs trading project.
How the certificate is earned
An assessed project: you select pairs from a universe with a documented method, trade them in an out-of-sample test with costs, and submit the code with a report. On a pass you receive the Course certificate in Pairs Trading, issued by the Institute with a verification code. Read how certification works.
Before you start
Working Python with pandas, regression, and the material of Time Series Analysis for Finance.
This course counts toward
Questions applicants ask
What is pairs trading?
Buying one instrument and selling a related one when the price gap between them is unusually wide, and closing both when the gap returns to normal. The position aims to profit from the gap, not from the direction of the market.
Is correlation enough to choose a pair?
No. Two prices can be highly correlated in returns while drifting apart for good. Cointegration tests whether the spread itself is stable, which is what a pairs trade relies on. The course shows both and where each fails.
Does pairs trading still work?
Published studies, including the Gatev, Goetzmann and Rouwenhorst study, report that returns from the simple distance method fell over time. The course tests that on recent data and shows what costs do to it.