Stochastic Mean Reversion Strategy (Python)

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.

• 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