Any Framework
Parabolic Sar Rsi Strategy (Python)
Published
Jul 19, 2025
1y ago
Total Downloads
587
587
Install
dotnet add package StockSharp.Strategies.0143_Parabolic_SAR_RSI.py --version 5.0.0
No framework information available.
README
Parabolic Sar Rsi Strategy (Python Version)
Strategy that combines Parabolic SAR for trend direction and RSI for entry confirmation with oversold/overbought conditions.
Here the Parabolic SAR outlines the prevailing trend and RSI measures exhaustion. Trades are opened once both indicators signal the same direction.
The combination is appealing to those who like trailing stops, since SAR also provides a dynamic exit. The stop placement follows the SAR curve.
Details
- Entry Criteria:
- Long:
Close > SAR && RSI < RsiOversold - Short:
Close < SAR && RSI > RsiOverbought
- Long:
- Long/Short: Both
- Exit Criteria:
- Long:
Close < SAR - Short:
Close > SAR
- Long:
- Stops: Uses Parabolic SAR as a trailing stop
- Default Values:
SarAf= 0.02mSarMaxAf= 0.2mRsiPeriod= 14RsiOversold= 30mRsiOverbought= 70mCandleType= TimeSpan.FromMinutes(5).TimeFrame()
- Filters:
- Category: Mean reversion
- Direction: Both
- Indicators: Parabolic SAR, Parabolic SAR, RSI
- Stops: Yes
- Complexity: Intermediate
- Timeframe: Mid-term
- Seasonality: No
- Neural Networks: No
- Divergence: No
- Risk Level: Medium
Adoption Assessment
A verified publisher signal is available. Assess fit from the package's supported frameworks, license and dependency graph rather than popularity alone.
No SPDX license expression is published. Review the license text and your organisation's policy before redistribution.No target framework metadata is available. Confirm compatibility in a representative project before standardising on this package.
Related Guides & Workflows
Learn how to evaluate, integrate, or audit this package in your .NET project.