StockSharp.Strategies.0222_Cointegration_Pairs.py

Cointegration Pairs Strategy (Python Version)

This strategy trades two assets that share a long-term cointegration relationship. By calculating the residual between the first asset and a beta-adjusted second asset, it looks for deviations that historically revert back to equilibrium.

Testing indicates an average annual return of about 103%. It performs best in the stocks market.

A long position buys the first asset and sells the second when the residual z-score drops below -EntryThreshold. A short position sells the first and buys the second when the z-score rises above the threshold. Positions are closed once the spread normalizes toward zero.

Cointegration pairs trading suits statistical arbitrageurs comfortable managing two instruments simultaneously. The built-in stop-loss protects against extreme moves if the relationship temporarily breaks down.

Details

• Entry Criteria:
  • Long: Residual Z-Score < -EntryThreshold
  • Short: Residual Z-Score > EntryThreshold
• Long/Short: Both sides.
• Exit Criteria:
  • Long: Exit when |Z-Score| < 0.5
  • Short: Exit when |Z-Score| < 0.5
• Stops: Yes, percentage stop-loss.
• Default Values:
  • Period = 20
  • EntryThreshold = 2.0m
  • Beta = 1.0m
  • StopLossPercent = 2.0m
  • CandleType = TimeSpan.FromMinutes(5)
• Filters:
  • Category: Arbitrage
  • Direction: Both
  • Indicators: Cointegration
  • Stops: Yes
  • Complexity: Intermediate
  • Timeframe: Intraday
  • Seasonality: No
  • Neural networks: No
  • Divergence: Yes
  • Risk Level: Medium