The robot monitors price action during a specific user-defined time window to establish daily high and low boundaries. Once this window closes, it executes buy or sell orders when the current price breaches these levels. The EA manages risk using fixed stop loss and take profit parameters and utilizes a fixed lot size. It also features a data generation component that exports price relative information to CSV files, facilitating external analysis or machine learning model development.
Session range breakout logic
Integrated CSV data generation for machine learning
Read from dataGen.mq5. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
filename_compra
string
datos_compra.csv
filename_venta
string
datos_venta.csv
SL_POINTS
int
6000
TP_POINTS
int
6000
HORA_ENTRADA
int
1
HORA_SALIDA
int
9
RELATIVOS_A_CONTAR
int
5
How to Install It
1Download the sourceUse "Download source (.zip)" above, or clone kecoma1/Athena 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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