Rsi Stochastic Strategy (Python)
Rsi Stochastic Strategy Strategy that combines RSI and Stochastic Oscillator for double confirmation of oversold and overbought conditions. Testing indicates an average annual return of about 181%. It...
Rsi Stochastic Strategy
Strategy that combines RSI and Stochastic Oscillator for double confirmation of oversold and overbought conditions.
Testing indicates an average annual return of about 181%. It performs best in the crypto market.
RSI provides a broader momentum view, while Stochastic gives faster signals near extremes. Trades flip as the oscillator crosses levels within the RSI context.
Ideal for nimble traders who favor oscillator setups. The strategy relies on an ATR stop to contain risk.
Details
- Entry Criteria:
- Long:
RSI < RsiOversold && StochK < StochOversold - Short:
RSI > RsiOverbought && StochK > StochOverbought
- Long:
- Long/Short: Both
- Exit Criteria:
- Long:
RSI > 50 - Short:
RSI < 50
- Long:
- Stops: Percent-based at
StopLossPercent - Default Values:
RsiPeriod= 14RsiOversold= 30mRsiOverbought= 70mStochPeriod= 14StochK= 3StochD= 3StochOversold= 20mStochOverbought= 80mStopLossPercent= 2.0mCandleType= TimeSpan.FromMinutes(5).TimeFrame()
- Filters:
- Category: Mean reversion
- Direction: Both
- Indicators: RSI, Stochastic Oscillator
- Stops: Yes
- Complexity: Intermediate
- Timeframe: Mid-term
- Seasonality: No
- Neural Networks: No
- Divergence: No
- Risk Level: Medium