How marco210210/ai-enhanced-hft works
This repository implements a MetaTrader 5 hybrid trading system: market data feeds an Expert Advisor (EA), which combines technical strategy signals with AI forecasts to size and manage trades. Forecasts are generated either in batch and saved as CSV, or served over TCP by the Python microservice. The README also documents H1 data export, three model families, and strategy-tester evaluation. EA internals and training workflows are not excerpted, so their relationships below rely on README statements rather than inspected implementation.
Main entry points: Hybrid_EA.mq5 Hybrid EA · forecast_RF.py Random Forest forecast · forecast_xgboost.py XGBoost forecast · forecast_lstm.py LSTM forecast
Components 20
Trading strategy
- Hybrid EA
Hybrid_EA.mq5 - Technical signals
Hybrid_EA.mq5 - Trade management
Hybrid_EA.mq5 - Forecast integration
Hybrid_EA.mq5
AI forecasting
- Random Forest forecast
model_rf/forecast_RF.py - XGBoost forecast
model_xgboost/forecast_xgboost.py - LSTM forecast
model_lstm/forecast_lstm.py - RF prepared data
model_rf/randomforest_ready_dataset.csv - XGBoost prepared data
model_xgboost/xgboost_ready_dataset.csv - LSTM prepared data
model_lstm/lstm_ready_dataset.csv - RF forecast CSV
model_rf/forecast_RF.csv - XGBoost forecast CSV
model_xgboost/forecast_XGBoost.csv - LSTM forecast CSV
model_lstm/forecast_lstm.csv - TCP AI service
socket_ai.py
Market data
- H1 exporter
Export_H1_Data.mq5 - H1 dataset
XAGUSD_H1_data.csv
Evaluation
- Backtest reports
backtest_ema6-24
Other components
- Market data
- MetaTrader 5
- Strategy Tester
Connections 18
- Market data → Hybrid EA: provides prices
README.md - MetaTrader 5 → Hybrid EA: runs
README.md - Hybrid EA → Technical signals: computes
README.md - Hybrid EA → Forecast integration: reads forecasts
README.md - Hybrid EA → Trade management: sizes and manages
README.md - H1 exporter → H1 dataset: exports
README.md - RF prepared data → Random Forest forecast: supplies features
model_rf/forecast_RF.py - Random Forest forecast → RF forecast CSV: writes
model_rf/forecast_RF.py - XGBoost prepared data → XGBoost forecast: supplies features
model_xgboost/forecast_xgboost.py - XGBoost forecast → XGBoost forecast CSV: writes
model_xgboost/forecast_xgboost.py - LSTM prepared data → LSTM forecast: supplies sequences
model_lstm/forecast_lstm.py - LSTM forecast → LSTM forecast CSV: writes
model_lstm/forecast_lstm.py - TCP AI service → Forecast integration: serves predictions
README.md - RF forecast CSV → Forecast integration: read during backtest
README.md - XGBoost forecast CSV → Forecast integration: read during backtest
README.md - LSTM forecast CSV → Forecast integration: read during backtest
README.md - Strategy Tester → Hybrid EA: backtests
README.md - Strategy Tester → Backtest reports: produces reports
README.md