Statistical Arbitrage in Practice: Building and Testing Pairs Strategies

The gap between understanding statistical arbitrage conceptually and being able to build and test a strategy is the gap between reading about pairs trading and actually running the numbers. This workbook course walks you through every stage of the pipeline with worked examples, decision checklists, and structured templates designed to make the process repeatable. By the end of this course you will be able to conduct a cointegration test on a candidate pair and interpret the results, calculate and plot a hedged spread using a regression-derived hedge ratio, build a Z-score signal with entry and exit thresholds, construct a simplified backtest accounting for transaction costs and slippage, and evaluate a pairs strategy using appropriate metrics including Sharpe ratio, maximum drawdown, and trade frequency. What you will learn: - Pair selection workflow: screening for economic relationship, running cointegration tests, and documenting results - Hedge ratio calculation: OLS regression method, interpretation of the slope, and rolling vs. static ratio comparison - Spread construction and normalization: building the Z-score series from a raw spread - Signal generation rules: entry threshold, exit threshold, and stop-loss level — and the trade-offs each involves - Backtest construction checklist: data handling, look-ahead bias prevention, and trade-by-trade P&L calculation - Transaction cost analysis: estimating commission, bid-ask spread, and market impact effects on net returns - Strategy metrics: calculating Sharpe ratio, Sortino ratio, and win rate from a trade log - Overfitting warning checklist: testing whether results are robust to small changes in parameters Each section provides a worked numerical example using a sample pair, followed by a template or worksheet you can apply to your own pair candidates. Case studies illustrate common pipeline errors — a pair that passes cointegration but diverges in live trading, a backtest inflated by survivorship bias, a hedge ratio that drifts over time and creates unintended directional exposure. Reflection prompts ask you to identify the problem before reading the diagnosis. This course is designed for quantitative finance students and algorithmic traders who want to build a statistical arbitrage strategy from scratch. Suitable for learners who are new to pairs trading but have some familiarity with financial data. This course is informational and educational and does not constitute financial or investment advice. All trading strategies involve risk of loss.