Gold REAVER
- Uzman Danışmanlar
- Moritz Henry Romberg
- Sürüm: 1.0
- Etkinleştirmeler: 10
Hello XAUUSD Fanatics,
Introducing: GOLD REAVER EA. (Performance of my $10k account with screenshots since February 23, 2025 available upon request - according to MQL-Market rules, I’m not allowed to include them here in the description - spoiler: they are very well)
The GOLD REAVER EA is a XAUUSD trading robot that operates completely WITHOUT GRID or MARTINGALE.
Features:
- No GRID
- No MARTINGALE
- Simulated account balance (The EA only uses as much money as desired - without missing out on scaling features!)
- Profit Target (Stops trading when the target is reached → Perfect for prop trading | my recommendation is to ALWAYS use this feature, even if it occasionally slightly limits profits. )
- Custom risk types (Fixed lot sizes or lots that scale with the account)
- Drawdown Manager (No running Drawdowns --> max. difference between balance and equity as input in %, if enabled)
- Works on multiple timeframes (M1,M10,M15,M30,H1 --> Generally, smaller timeframes = higher risk)
With just the right amount of inputs, the trading robot can be perfectly tailored and customized to your preferences.
(I am open to ideas on expanding the available inputs to make the EA even more adaptable)
The GOLD REAVER works best in sideways or, even better, rising gold markets!
Of course, this EA carries risk, but you have full control over how much risk you take, thanks to the simulated account balance, risk type selection, and more.
High-Risk-High-Reward or Slow-and-Steady? Both can work, and both are possible with the GOLD REAVER EA!
PS: The "higher" drawdowns are mainly caused by the EA's scaling features and can be perfectly controlled through an appropriate profit target and simulated account balance.
Additionally, please note that the minimum lot size for XAUUSD is 0.01, and therefore, an account size of at least $1000 is recommended (but not required).
.set files available on request → for High-Risk-High-Reward, Slow-and-Steady, or a balanced approach
