The primary files utilize the MQL5 standard library classes to combine trend-following signals, such as Moving Average crossovers, with volatility-based exits like the Parabolic SAR trailing stop. The project includes risk management modules for lot size optimization based on account equity and a decrease factor for consecutive losses. Although the documentation refers to AI components, the code implementation centers on classic oscillators like Stochastic and trend filters like ADX.
Read from ExpertMAPSARSizeOptimized.mq5. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
Inp_Expert_Title
string
ExpertMAPSARSizeOptimized
Inp_Signal_MA_Period
int
12
Inp_Signal_MA_Shift
int
6
Inp_Signal_MA_Method
ENUM_MA_METHOD
MODE_SMA
Inp_Signal_MA_Applied
ENUM_APPLIED_PRICE
PRICE_CLOSE
Inp_Trailing_ParabolicSAR_Step
double
0.02
Inp_Trailing_ParabolicSAR_Maximum
double
0.2
Inp_Money_SizeOptimized_DecreaseFactor
double
3.0
Inp_Money_SizeOptimized_Percent
double
10.0
How to install it
1Download the sourceUse "Download source (.zip)" above, or clone Uzochinny/forex-ai-bot 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, and any .mqh files into the Include folder the code expects.
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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