Parabolic Sar Stochastic Strategy (Python)

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). 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.

• Entry Criteria:

• Long: Close > SAR && StochK < StochOversold

• Short: Close < SAR && StochK > StochOverbought []Long/Short: Both []Exit Criteria:

• Parabolic SAR flip in opposite direction []Stops: Dynamic SAR based []Default Values:

• AccelerationFactor = 0.02m

• MaxAccelerationFactor = 0.2m

• StochK = 3

• StochD = 3

• StochPeriod = 14

• StochOversold = 20m

• StochOverbought = 80m

• CandleType = 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