StockSharp.Strategies.0220_Volatility_Breakout.py

Volatility Breakout Strategy (Python Version)

The Volatility Breakout strategy seeks strong directional moves when price escapes from its average range. By measuring the distance from a simple moving average using the Average True Range, the algorithm defines breakout thresholds that scale with volatility.

Testing indicates an average annual return of about 97%. It performs best in the crypto market.

A buy order is triggered when the close rises above the SMA by more than Multiplier times the ATR. A sell signal appears when the close falls below the SMA by the same distance. Positions remain open until an opposite breakout occurs or a protective stop is hit.

This technique caters to intraday traders who thrive on momentum surges. Using ATR-based thresholds helps filter out noise so only significant moves generate trades.

Details

• Entry Criteria:
  • Long: Close > SMA + Multiplier * ATR
  • Short: Close < SMA - Multiplier * ATR
• Long/Short: Both sides.
• Exit Criteria:
  • Long: Exit when an opposite breakout triggers or stop-loss hits
  • Short: Exit when an opposite breakout triggers or stop-loss hits
• Stops: Yes, stop-loss at Multiplier * ATR from entry.
• Default Values:
  • Period = 20
  • Multiplier = 2.0m
  • CandleType = TimeSpan.FromMinutes(5)
• Filters:
  • Category: Breakout
  • Direction: Both
  • Indicators: SMA, ATR
  • Stops: Yes
  • Complexity: Intermediate
  • Timeframe: Intraday
  • Seasonality: No
  • Neural networks: No
  • Divergence: No
  • Risk Level: Medium