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dotnet add package StockSharp.Strategies.0167_Keltner_RSI.py --version 5.0.1

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README

Keltner Rsi Strategy (Python Version)

Strategy combining Keltner Channels and RSI indicators. Looks for mean reversion opportunities when price touches channel boundaries and RSI confirms oversold/overbought conditions.

Testing indicates an average annual return of about 88%. It performs best in the stocks market.

Keltner Channels map recent volatility while RSI measures momentum extremes. Entries occur when RSI supports a move beyond the channel.

Great for bounce traders around volatility envelopes. Stops rely on an ATR multiplier.

Details

  • Entry Criteria:
    • Long: Close < LowerBand && RSI < RsiOversoldLevel
    • Short: Close > UpperBand && RSI > RsiOverboughtLevel
  • Long/Short: Both
  • Exit Criteria:
    • Price returns to EMA
  • Stops: Percent-based using StopLossPercent
  • Default Values:
    • EmaPeriod = 20
    • AtrPeriod = 14
    • AtrMultiplier = 2.0m
    • RsiPeriod = 14
    • RsiOverboughtLevel = 70m
    • RsiOversoldLevel = 30m
    • StopLossPercent = 2.0m
    • CandleType = TimeSpan.FromMinutes(5).TimeFrame()
  • Filters:
    • Category: Mean reversion
    • Direction: Both
    • Indicators: Keltner Channel, RSI
    • Stops: Yes
    • Complexity: Intermediate
    • Timeframe: Mid-term
    • Seasonality: No
    • Neural Networks: No
    • Divergence: No
    • Risk Level: Medium

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