Pair Trading Strategies

Market-neutral strategies that profit from relative price movements between correlated assets

Your Progress

0 / 5 completed
Previous Module
Mean Reversion Strategies

Market-Neutral Trading

Pair trading is a market-neutral strategy that profits from the relative price movements of two correlated securities. Instead of betting on market direction (up or down), you bet on the spread between two related assets returning to its historical average.

When the spread widens (one stock outperforms), you short the outperformer and buy the underperformer. When the spread narrows back to normal, you profit from both positions. This strategy is used by hedge funds managing billions and individual traders alike.

Why Pair Trading Works

📊

Statistical Relationship

Similar companies (Coca-Cola vs Pepsi, Ford vs GM) tend to move together due to shared industry factors. Temporary divergences create profit opportunities.

🛡️

Market Neutrality

By going long and short simultaneously, you hedge out market risk. If the market crashes, your short position gains offset long losses.

🔄

Mean Reversion

Price spreads tend to revert to historical averages. Deviations are temporary - caused by news, sentiment, or liquidity - not fundamental changes.

High Frequency

Spreads can normalize quickly (hours to days). Multiple trades per month generate consistent returns with lower risk than directional bets.

💡 Example: GM vs Ford

Day 1: GM trades at $40, Ford at $12. Historical spread is $28. Current spread is $28 (normal).

Day 10: GM drops to $38, Ford rises to $14. Spread narrows to $24 (abnormal divergence).

Trade Setup: Short Ford ($14) and long GM ($38). Betting spread will widen back to $28.

Day 20: GM recovers to $42, Ford falls to $14. Spread returns to $28. Close both positions for profit.

Profit: GM gain ($4) + Ford short gain ($0) = $4 per pair, regardless of overall market direction.

Key Requirements for Pair Trading

High Correlation: Stocks must move together (correlation > 0.70). Without correlation, spread changes are random, not mean-reverting.
Cointegration: Prices must be linked long-term, not just temporarily correlated. Test with statistical methods like Engle-Granger.
Similar Fundamentals: Same industry, comparable size, shared risk factors. Avoid pairing unrelated stocks even if statistically correlated.
Sufficient Liquidity: Must be able to enter/exit both positions quickly. Illiquid stocks create slippage and execution risk.