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A-share low-frequency quantitative trading framework covering research, backtesting, and execution

Project description

DeltaFQ

中文 | English

Version Platform Python Build License

Python Open-source Quantitative Framework: Covering the full "Research, Backtest, Trade" lifecycle, building an industrial-grade closed-loop quantitative workflow from scratch to production.

Strategy Signals Backtest Overview

🎓 Official Tutorials

iMOOC - AI Quantitative System Course

Official Course: Deeply deconstructing the framework's architecture from 0 to 1, covering live trading logic and industrial-grade quantitative development. An essential course for mastering DeltaFQ.

📦 Installation

pip install deltafq

✨ Key Features

  • 📥 Multi-source Data - Global multi-market historical/real-time data, ready to use
  • 🧠 Rapid Development - Signal-driven architecture, fast implementation with strategy templates
  • 📉 Professional Backtesting - High-performance matching engine, deep performance metrics and analysis
  • ⚡ Event-driven - Second-level market data distribution, millisecond-level Tick signal processing
  • 🤖 Live Gateway - Pluggable adapters, seamless switching between simulation and live trading

⚡ Quick Start

import deltafq as dfq

# 1. Define strategy logic
class MyStrategy(dfq.strategy.BaseStrategy):
    def generate_signals(self, data):
        bands = dfq.indicators.TechnicalIndicators().boll(data["Close"])
        return dfq.strategy.SignalGenerator().boll_signals(data["Close"], bands)

# 2. Minimal backtest & results
engine = dfq.backtest.BacktestEngine()
engine.set_parameters("GOOGL", "2025-07-26", "2026-01-26")
engine.load_data()
engine.add_strategy(MyStrategy(name="BOLL"))
engine.run_backtest()
engine.show_report()
engine.show_chart(use_plotly=False)

🚀 Application Example

DeltaFStation is an open-source quantitative trading cloud platform based on deltafq, integrating data services, strategy management, and trading access with paper and live support. Project: https://github.com/Delta-F/deltafstation/

DeltaFStation Architecture DeltaFStation Backtest Engine

🔌 Interface Integration

  • yfinance ✅ - US, A-shares, HK, Crypto, Indices
  • eastmoney ✅ - OTC Funds (Index, QDII, Stock, Bond, Mixed)
  • PaperTrade ✅ - Local simulation, position management, order management, data persistence
  • QMT API 🛠️ - Market data and live trading interfaces

🏗️ Project Architecture

deltafq/
├── data        # Data acquisition, cleaning, storage interfaces (stocks, funds)
├── indicators  # Technical indicators and factor calculations
├── strategy    # Signal generators and strategy base classes
├── backtest    # Backtest execution, performance metrics, reporting
├── live        # Event engine, gateway abstraction, routing
├── adapters    # Pluggable data/trade adapters
├── trader      # Execution with order/position management
└── charts      # Signal/performance chart components
Project Architecture Workflow

🤝 Contributing

  • Feedback: Bug reports and contributions are welcome via Issue or Pull Requests.
  • WeChat Official Account: Follow DeltaFQ开源量化 for updates, strategies, and quantitative resources.

WeChat Official Account

📄 License

MIT License. See LICENSE for details.

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