StockSharp.Strategies.0233_Beta_Neutral_Arbitrage.py

Beta Neutral Arbitrage Strategy (Python Version)

This strategy seeks to exploit pricing differences between two securities while neutralizing overall market beta. By adjusting positions based on each asset's beta to a common index, the portfolio aims to remain insensitive to broad market moves.

Testing indicates an average annual return of about 52%. It performs best in the crypto market.

A long spread goes long the asset with lower beta-adjusted price and shorts the other when the spread deviates beyond two standard deviations. A short spread does the reverse when the spread is above the mean. Trades are closed once the beta-adjusted spread reverts toward its average.

Beta neutral arbitrage is common among hedge funds looking for relative value without taking directional risk. A stop-loss is applied if the spread continues to widen instead of converging.

Details

• Entry Criteria:
  • Long: Beta-adjusted spread < Mean - 2*StdDev
  • Short: Beta-adjusted spread > Mean + 2*StdDev
• Long/Short: Both sides.
• Exit Criteria:
  • Long: Exit when spread approaches mean
  • Short: Exit when spread approaches mean
• Stops: Yes, percent stop-loss.
• Default Values:
  • CandleType = TimeSpan.FromMinutes(5)
  • LookbackPeriod = 20
  • StopLossPercent = 2m
• Filters:
  • Category: Arbitrage
  • Direction: Both
  • Indicators: Beta-adjusted spread
  • Stops: Yes
  • Complexity: Advanced
  • Timeframe: Intraday
  • Seasonality: No
  • Neural networks: No
  • Divergence: Yes
  • Risk Level: High