The primary robot utilizes a hybrid logic, combining traditional indicators like ADX and the Bill Williams Alligator with external artificial intelligence models for market analysis. It includes comprehensive risk controls such as prop firm drawdown protection, daily loss limits, and equity targets. While it offers standard lot sizing, users can enable martingale scaling. The repository also contains various specialized tools for grid trading, RSI divergence, and channel analysis.
AI-powered market analysis via external LLM APIs
Prop firm risk management with daily drawdown limits
Multi-indicator strategy using ADX and Alligator
Python FastAPI dashboard for strategy monitoring
Optional martingale lot scaling and trailing stops
Account Type (Standard Broker / Prop Firm / Funded)
InpUseMoneyFilter
bool
true
Enable Money Filter
InpEquityProfitTarget
double
5000.0
Profit Target — Stop when Equity >= this ($)
InpEquityLossLimit
double
2500.0
Loss Limit — Stop when Equity <= this ($)
InpPropInitBalance
double
0
Challenge Initial Balance (0 = auto-detect)
InpPropRiskUnit
ENUM_PROP_RISK_UNIT
PROP_UNIT_PERCENT
Risk Unit — use % or $ for values below
InpPropDailyProfitTarget
double
2.0
Daily Profit Target (% or $, 0 = disabled)
InpPropDailyLossLimit
double
5.0
Daily Loss Limit / Max Daily Drawdown (% or $)
InpPropMaxTotalDrawdown
double
10.0
Max Total Drawdown (% or $)
InpPropUseTrailingDrawdown
bool
false
Enable Trailing Drawdown (high-water-mark based)
InpPropChallengeTarget
double
0
Overall Challenge Profit Target (% or $, 0 = disabled)
InpRiskMode
ENUM_RISK_MODE
RISK_FIXED_LOT
Risk Mode
InpFixedLot
double
0.01
Fixed Lot Size
InpRiskPercent
double
1.0
Risk Percent
InpRiskMoney
double
50.0
Risk Amount ($)
InpMaxLot
double
5.0
Maximum Lot Cap
InpMinLot
double
0.01
Minimum Lot Size
InpUseMartingale
bool
false
Enable Martingale
InpMartingaleMultiplier
double
2.0
Lot Multiplier After Loss
How to install it
1Download the sourceUse "Download source (.zip)" above, or clone akshayboora342-cell/moneymaker from GitHub, and unzip it.
2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL5/Experts.
3Copy the filesCopy the .mq5 file into Experts.
4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.
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