StockSharp.Strategies.0237_Stochastic_Mean_Reversion.py

Stochastic Mean Reversion Strategy (Python Version)

This strategy measures the Stochastic oscillator against its own moving average to locate overextended swings. When %K moves several standard deviations away from its mean, the expectation is for the indicator to drift back toward typical values.

A long trade is placed when Stochastic %K falls below the lower band defined by the average minus Multiplier times the standard deviation. A short trade occurs when %K exceeds the upper band. Positions are closed once %K crosses back through its average line.

The method is designed for short-term traders who like to trade overbought and oversold extremes. The stop-loss protects against sustained momentum that fails to mean revert.

Details

• Entry Criteria:
  • Long: %K < Avg - Multiplier * StdDev
  • Short: %K > Avg + Multiplier * StdDev
• Long/Short: Both sides.
• Exit Criteria:
  • Long: Exit when %K > Avg
  • Short: Exit when %K < Avg
• Stops: Yes, percent stop-loss.
• Default Values:
  • StochPeriod = 14
  • KPeriod = 3
  • DPeriod = 3
  • AveragePeriod = 20
  • Multiplier = 2.0m
  • CandleType = TimeSpan.FromMinutes(5)
• Filters:
  • Category: Mean Reversion
  • Direction: Both
  • Indicators: Stochastic Oscillator
  • Stops: Yes
  • Complexity: Intermediate
  • Timeframe: Intraday
  • Seasonality: No
  • Neural networks: No
  • Divergence: No
  • Risk Level: Medium