Pairs trading is a market-neutral strategy that focuses on the relative performance of two correlated assets instead of predicting overall market direction. Professional traders use this approach to take advantage of temporary price deviations between two securities while keeping risk relatively low. In this guide, we’ll explore how professionals build a pairs trading example strategy step by step.
Understanding Pairs Trading
Pairs trading works by identifying two assets that historically move together—often called a correlated pair. When the relationship between these two assets temporarily diverges, traders can:
- Buy the undervalued asset
- Short the overvalued asset
Profit is earned when the prices converge back to their normal relationship. This approach is called mean reversion trading and is used extensively in stocks, forex, and cryptocurrencies.
Step 1: Selecting a Strong Pair
Professional traders start by researching potential pairs with stable correlations. A strong pair should have:
- High historical correlation (usually above 0.75)
- Similar sector or economic drivers
- Sufficient liquidity for trading
Example: Consider Apple (AAPL) and Microsoft (MSFT), two technology giants that often move together. Historical data shows their price ratio tends to stay within a predictable range, making them ideal candidates for a pairs trading example strategy.
Step 2: Analyzing the Spread
Once the pair is selected, professionals calculate the spread—the difference in price or the ratio between the two assets. Tools like TradingView or Python scripts can help visualize the spread over time.
- Spread = Price of Asset A – Price of Asset B
- Mean of the spread = Average historical spread
- Standard deviation = Measures how far current spread deviates from the mean
These calculations allow traders to identify overextended conditions that signal potential trades.
Step 3: Defining Entry and Exit Rules
A professional pairs trading strategy is systematic. Traders set clear rules:
- Entry: Buy the undervalued asset and short the overvalued asset when the spread exceeds a certain threshold (e.g., two standard deviations from the mean)
- Exit: Close the trade when the spread returns to the mean
- Stop-loss: Implement a maximum allowed loss if the spread moves further against the position
Example Trade:
- Spread between AAPL and MSFT reaches +2 standard deviations
- Enter: Short AAPL, Buy MSFT
- Exit: Spread returns to mean
Step 4: Position Sizing and Risk Management
Professionals focus on risk management to protect capital. Key considerations include:
- Equal dollar allocation to each side of the trade
- Adjusting positions based on volatility
- Limiting risk per trade (e.g., 1–2% of total portfolio)
- Avoiding trading during earnings or high-impact news
This ensures the portfolio remains balanced even if one trade moves against expectations.
Step 5: Portfolio Diversification
Instead of relying on a single pair, professionals create a pairs trading portfolio:
- Include multiple pairs across different sectors
- Ensure low correlation between pairs to reduce overall portfolio risk
- Monitor all spreads and correlation levels continuously
Diversification increases the chances of consistent profits while minimizing the impact of unexpected market moves.
Step 6: Backtesting and Monitoring
Backtesting is critical. Professionals test their pairs trading strategy on historical data to:
- Validate spread behavior
- Check entry and exit rules
- Measure potential returns and drawdowns
After live trading begins, continuous monitoring ensures trades are executed correctly and adjustments are made if correlations break down.
Final Thoughts
A professional pairs trading example strategy is all about structure, discipline, and data-driven decisions. By carefully selecting correlated pairs, calculating spreads, setting clear entry and exit rules, managing risk, and diversifying the portfolio, traders can reduce market exposure while creating consistent opportunities.
Whether in stocks, forex, or crypto, mastering pairs trading allows professionals to profit from relative price movements and build a strategy that is systematic, predictable, and resilient—even in volatile markets.
