Quant Trading Framework

This is a professional-grade modular framework for backtesting and live trading of Bitcoin strategies. It supports classical strategies, machine learning models, and real-time Binance integration.

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📦 Project Structure

├── setup.py
├── README.md
├── requirements.txt
├── .vscode/
│   └── launch.json
├── Quantlib/
│   ├── __init__.py
│   ├── backtest/
│   │   ├── engine.py
│   │   ├── metrics.py
│   │   └── ...
│   ├── strategies/
│   │   ├── sma_crossover.py
│   │   ├── rsi_reversion.py
│   │   └── ...
│   ├── indicators/
│   │   ├── sma.py
│   │   ├── macd.py
│   │   └── ...
│   └── ...
├── py_example/
│   ├── run_backtest_sma.py
│   ├── Train_XGBoost_and_Backtest.py
│   └── ...
├── notebook_example/
│   ├── 01_train_xgboost.ipynb
│   └── ...
├── data/
│   └── BTCUSDT.csv

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✅ Installation (Recommended)

Make sure you are using Python >= 3.8. Then run:

cd gptquant_project

# Install dependencies
pip install -r requirements.txt

# Install project as editable module
pip install -e .

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🧪 Run Examples

Run a backtest:

python py_example/run_backtest_sma.py

Train & backtest with ML:

python py_example/Train_XGBoost_and_Backtest.py

Explore in notebooks:

Open any notebook in notebook_example/ with Jupyter.

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📡 Live Trading

To switch from backtest to live execution:

from Quantlib.execution import TradeExecutor
executor = TradeExecutor(mode="live", broker="binance")

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🧠 Troubleshooting

• If you get ModuleNotFoundError, run pip install -e .
• In VS Code, use .vscode/launch.json to ensure cwd is set to project root

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Set proxy for local to check in code when connecting VPN git config --global http.proxy 'http://127.0.0.1:7890' git config --global https.proxy 'http://127.0.0.1:7890'

unset: git config --global --unset http.proxy git config --global --unset https.proxy