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+# 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
+
+```bash
+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:**
+```bash
+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%)