profitable-expert-advisor/ai/eurusd1min

EURUSD 15-Minute ONNX Model Training

This directory contains the training script for a EURUSD price prediction model using 15-minute timeframe data from 1990 to 2026 using MetaTrader 5 as the data source.

Requirements

pip install MetaTrader5 tensorflow scikit-learn pandas numpy tf2onnx onnx tqdm

Usage

1. Make sure MetaTrader 5 is running and logged in

2. Ensure EURUSD symbol is available in your broker

3. Make sure you have historical data downloaded in MT5 (Tools → History Center → Download)

4. Run the training script:

cd ai/eurusd1min
python main.py

Configuration

The script is configured with:

• Symbol: EURUSD
• Timeframe: M15 (15 minutes)
• Lookback: 60 bars (15 hours of history)
• Date Range: 1990-01-01 to 2026-01-01
• Model Architecture: LSTM with 3 layers (128, 64, 32 units)
• Epochs: 50 (with early stopping)
• Batch Size: 64

Data Fetching

• The script fetches data in 1-month chunks to manage memory
• 15-minute data is more likely to be available for longer historical periods than 1-minute data
• The script automatically skips chunks with only 1 bar (invalid/placeholder data)
• Progress is shown for each chunk
• Make sure you have sufficient historical data in MT5

Output

The script will create:

• models/EURUSD_M15_model.onnx - The trained ONNX model
• models/EURUSD_M15_model_scaler.pkl - The MinMaxScaler used for normalization

Model Features

The model uses 13 features:

1. Open
2. High
3. Low
4. Close
5. Tick Volume
6. RSI (14 period)
7. EMA 20
8. EMA 50
9. ATR (14 period)
10. Price Change (percentage)
11. High/Low Ratio
12. Volume MA (20 period)
13. Volume Ratio

Model Output

The model predicts the price change percentage for the next bar (15 minutes ahead).

Notes

• Training on 36 years of 15-minute data will take significant time and memory
• The script fetches data in 1-month chunks to manage memory
• Chunks with only 1 bar are automatically skipped (invalid/placeholder data)
• Early stopping and learning rate reduction are enabled to prevent overfitting
• The model uses dropout (0.3) for regularization
• 15-minute data is more manageable than 1-minute data for long historical periods

Using the Model in MQL5

Expert Advisor

An Expert Advisor (EURUSD_M15_EA.mq5) is provided in this directory. It uses the trained ONNX model for automated trading.

Setup:

1. Copy EURUSD_M15_model.onnx to MQL5/Files/ directory
2. Compile EURUSD_M15_EA.mq5 in MetaEditor
3. The model will be embedded as a resource during compilation
4. Attach the EA to a EURUSD chart with M15 timeframe

Features:

• Embedded ONNX model (no file path issues)
• Dynamic SL/TP based on prediction, confidence, and ATR
• Configurable prediction threshold and confidence filter
• Automatic position management

Input Parameters:

• InpLookback: 60 bars (15 hours of history)
• InpUsePredictedSLTP: Use dynamic SL/TP based on prediction
• InpPredictionThreshold: Minimum prediction change to trade (default: 0.00005 = 0.005%)
• InpMinConfidence: Minimum confidence to trade (default: 0.1 = 10%)