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Parabolic SAR RSI Divergence (Python)
Published
Jul 20, 2025
1y ago
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dotnet add package StockSharp.Strategies.0336_Parabolic_SAR_RSI_Divergence.py --version 5.0.0
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README
Parabolic SAR RSI Divergence (Python Version)
The Parabolic SAR RSI Divergence strategy is built around that trades based on Parabolic SAR signals when RSI shows divergence from price.
Signals trigger when Parabolic confirms divergence setups on intraday (5m) data. This makes the method suitable for active traders.
Stops rely on ATR multiples and factors like SarAccelerationFactor, SarMaxAccelerationFactor. Adjust these defaults to balance risk and reward.
Details
- Entry Criteria: see implementation for indicator conditions.
- Long/Short: Both directions.
- Exit Criteria: opposite signal or stop logic.
- Stops: Yes, using indicator-based calculations.
- Default Values:
SarAccelerationFactor = 0.02mSarMaxAccelerationFactor = 0.2mRsiPeriod = 14CandleType = TimeSpan.FromMinutes(5).TimeFrame()
- Filters:
- Category: Trend following
- Direction: Both
- Indicators: Parabolic, Divergence
- Stops: Yes
- Complexity: Intermediate
- Timeframe: Intraday (5m)
- Seasonality: No
- Neural Networks: No
- Divergence: Yes
- Risk Level: Medium
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