Logo de "FadeBreakout.Ver1"
FadeBreakout.Ver1
0.0
15/07/2025
0
Desktop, Mobile, Web
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🧠 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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