LSTM Neural Network Trader functions as a proof-of-concept system where MT5 exports market data to CSV files, which are then processed by an external Python environment using PyTorch. The system requires manual configuration of screen coordinates for one-click trading buttons and utilizes memory address reading via third-party tools to facilitate communication between Python and the terminal. It includes modules for data collection, training, and live execution, primarily targeting the DE30 index.
Long Short Term Memory neural network architecture
External Python integration using PyTorch models
Automated market data exportation for training
Coordinate-based trade execution via GUI interaction
1Download the sourceUse "Download source (.zip)" above, or clone TestovironPowroci/LSTM-on-MetaTrader5 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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