Parabolic Sar Stochastic Strategy (C#)
Parabolic Sar Stochastic Strategy Implementation of strategy - Parabolic SAR + Stochastic. Buy when price is above SAR and Stochastic %K is below 20 (oversold). Sell when price is below SAR and Stocha...
Install-Package StockSharp.Strategies.0158_Parabolic_SAR_Stochastic -Version 5.0.2
Parabolic Sar Stochastic Strategy
Implementation of strategy - Parabolic SAR + Stochastic. Buy when price is above SAR and Stochastic %K is below 20 (oversold). Sell when price is below SAR and Stochastic %K is above 80 (overbought).
Testing indicates an average annual return of about 61%. It performs best in the crypto market.
Parabolic SAR supplies the trend and Stochastic refines entry on pullbacks. Signals flip when SAR changes side.
A straightforward trend strategy with built-in SAR stops. ATR settings handle additional risk control.
Details
- Entry Criteria:
- Long:
Close > SAR && StochK < StochOversold - Short:
Close < SAR && StochK > StochOverbought
- Long:
- Long/Short: Both
- Exit Criteria:
- Parabolic SAR flip in opposite direction
- Stops: Dynamic SAR based
- Default Values:
AccelerationFactor= 0.02mMaxAccelerationFactor= 0.2mStochK= 3StochD= 3StochPeriod= 14StochOversold= 20mStochOverbought= 80mCandleType= TimeSpan.FromMinutes(5).TimeFrame()
- Filters:
- Category: Mean reversion
- Direction: Both
- Indicators: Parabolic SAR, Parabolic SAR, Stochastic Oscillator
- Stops: Yes
- Complexity: Intermediate
- Timeframe: Mid-term
- Seasonality: No
- Neural Networks: No
- Divergence: No
- Risk Level: Medium