🧠 Logic Overview — Fade Breakout Ultimate (H1 ProPlus Edition)
This cBot is a counter-trend breakout fading strategy designed for the cTrader platform. It uses Donchian Channel and ATR-based dynamic risk management with a high watermark capital protection model.
📋 Core Features
1. Entry Logic
- Uses Donchian Channel (default period: 5) to detect breakouts.
- Sell: If the previous candle closed below the upper band and the current candle closes above it (false breakout upward).
- Buy: If the previous candle closed above the lower band and the current candle closes below it (false breakout downward).
- Entries are reversed against the breakout direction (fade strategy).
2. Volume Calculation (Position Sizing)
- Two modes:
- Fixed Lot
- Risk Percentage: Based on a high watermark (the peak balance recorded so far), to prevent risk escalation during drawdowns.
- SL in pips is calculated via ATR × SL Multiplier.
3. Take Profit / Stop Loss
- Initial TP is based on ATR × TP Multiplier (default: 1.9).
- When TP is hit:
- Half of the position is closed.
- Remaining half is secured with break-even stop loss.
- If TP is cleared, trailing stop is activated using ATR × Trailing Multiplier.
4. Cool Down Mechanism (Loss Control)
- If a defined number of consecutive losses (e.g., 5) occur:
- The bot stops trading for a set number of bars (cool-down period, e.g., 6 H1 candles).
- This protects against overtrading during volatile or adverse market conditions.
⚙️ Key Parameters Explained
GroupParameterDescription
Risk
LotSizingMode, FixedLotSize, RiskPercentage
Defines how position size is calculated
Entry
DonchianPeriod, AtrPeriod
Sets breakout detection and volatility window
SL/TP
SlAtrMultiplier, FirstTpAtrMultiplier, TrailingStopAtrMultiplier
Controls SL/TP/trailing behavior relative to ATR
Safety
EnableCoolDown, MaxConsecutiveLosses, CoolDownBars
Loss protection settings
✅ Best Use Cases
- Works best in range-bound markets with frequent false breakouts.
- Ideal for symbols like EUR/USD, AUD/USD, or EUR/GBP.
- Should be backtested and optimized per symbol/timeframe.
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