Scalping Robot ML incorporates a machine learning signal filter, requiring a separate Python environment to classify high-probability trade setups using historical market data. The robot manages entries within specific time windows and limits the total number of concurrent positions. Risk management is handled through fixed stop loss and take profit targets, supplemented by a trailing stop mechanism that activates after a predefined profit threshold is met.
Read from ScalpingBot.mq5. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
BarsN
int
10
number of bars to look back
Tppoints
int
230
take profit (10 points = 1 pip)
Slpoints
int
25
stoploss points (10 points = 1 pip)
TslTriggerPoints
int
25
points in profit before trailing SL is activated
TslPoints
int
10
trailing stoploss (10 points = 1 pip)
Timeframe
ENUM_TIMEFRAMES
PERIOD_CURRENT
timeframe to run
InpMagic
int
292929
EA identification number
TradeComment
string
scalping robot
MaxTrades
int
10
maximum number of open positions
SHInput
StartHour
10
time to start trading
EHInput
EndHour
22
time to stop trading
How to install it
1Download the sourceUse "Download source (.zip)" above, or clone Red-misst/mql5 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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