📈 QuantEval

中文说明 / Chinese Guide · 贡献指南 / Contributing

QuantEval is a lightweight, friendly Python toolkit for researching Chinese A-share and Hong Kong (HKEX) strategies, factors, and benchmark comparisons. We've combined a reusable package under src/quanteval, tutorial notebooks, and automated workflows to make your quant journey smoother! 🚀

✨ Highlights

• ⏱️ Backtesting engine with delayed signal execution to keep things realistic (no look-ahead bias here!).
• 🤖 Built-in strategies: Classic strategies like Dual Moving Average, Bollinger Mean Reversion, and consistent Buy-and-Hold... Full set in 👉 src/quanteval/strategies
• 🔀 Strategy Comparison: Multi-strategy correlation analysis, ranking, and equal-weight portfolio construction.
• 📊 Technical factors: From SMA and RSI to MACD, ATR, and more.
• 🔍 Optimization: Grid-search and walk-forward analysis to fine-tune your ideas.
• 🎨 Visualization: Pretty static and interactive plots for your equity curves.
• 💾 Data Caching: Native support for A-share (AkShare) and Hong Kong market (yfinance) stock, ETF, and index data.

🛠️ Installation

📦 From PyPI

The package is available on PyPI. Install the latest released version with:

pip install quanteval

🔨 End users (install from source)

git clone https://github.com/KarhouTam/quanteval.git
cd quanteval
python -m pip install .

🧑‍💻 Contributors

git clone https://github.com/KarhouTam/quanteval.git
cd quanteval
python -m pip install -e ".[dev]"

🚀 Quick start

Ready to run your first backtest? It's as simple as this:

from quanteval import Backtester, DataLoader, DualMAStrategy

# 1. Grab some data 🏪
loader = DataLoader()
data = loader.load_stock('600519', '20200101', '20231231')

# 2. Pick a strategy 🧠
strategy = DualMAStrategy(fast_window=10, slow_window=60)

# 3. Let's see how it performed! 📊
results = Backtester(strategy=strategy, data=data, transaction_costs=True).run()

print(results.summary())
results.plot()

📖 More examples

Check out these notebooks to level up:

• examples/01_quickstart.ipynb: Basic data loading and first backtest 🏃
• examples/02_parameter_optimization.ipynb: Finding the best parameters 🎯
• examples/03_strategy_comparison.ipynb: Battle of the strategies ⚔️
• examples/04_hk_market_support.ipynb: Trading in the Hong Kong market 🇭🇰
• TUTORIAL_EN.md: Deep dive tutorial 📚