Bollinger Stochastic Strategy (Python)

Bollinger Stochastic pairs Bollinger Bands with the stochastic oscillator to identify overextended moves. Price touching the outer band while the oscillator is in an extreme zone suggests a possible snap back. The system fades those extremes, going long when price hits the lower band with stochastic oversold, and shorting the upper band with stochastic overbought. A percent-based stop limits risk if the mean reversion fails to occur.

• Entry Criteria: indicator signal

• Long/Short: Both

• Exit Criteria: stop-loss or opposite signal

• Stops: Yes, percent based

• Default Values:

• CandleType = 15 minute

• StopLoss = 2% [*]Filters:

• Category: Mean reversion

• Direction: Both

• Indicators: Bollinger Bands, Stochastic

• Stops: Yes

• Complexity: Intermediate

• Timeframe: Intraday

• Seasonality: No

• Neural networks: No

• Divergence: No

• Risk level: Medium