Multi-Timeframe Bollinger Bands Strategy (Python)

Applies Bollinger Bands on both a primary and a higher timeframe. Trades when price pierces the higher timeframe bands and optionally filters entries with a long-term moving average. The goal is to fade extremes against the broader trend. The strategy supports both long and short positions. A stop-loss percentage can be enabled for risk management. Using multiple timeframes helps to avoid trades against dominant market structure.

• Entry Criteria:

• Long: Close below the higher timeframe lower band and above the MA filter (if enabled).

• Short: Close above the higher timeframe upper band and below the MA filter (if enabled). [*]Exit Criteria:

• Long: Price closes above the current timeframe upper band.

• Short: Price closes below the current timeframe lower band. [*]Indicators:

• Bollinger Bands on two timeframes (length 20, multiplier 2)

• Optional EMA filter (period 200) []Stops: Optional stop-loss via StartProtection (% based). []Default Values:

• BBLength = 20

• BBMultiplier = 2.0

• UseMaFilter = False

• MaLength = 200

• SLPercent = 2 [*]Filters:

• Counter-trend with MTF context

• Timeframe: main 5m, MTF 60m by default

• Indicators: Bollinger Bands, EMA

• Stops: optional

• Complexity: Moderate