FactorHub

FactorHub is an open-source modern quantitative factor analysis platform designed specifically for the Chinese A-share market.

FactorHub = Factor + Hub

A full-stack quantitative investment research system integrating factor management, analysis, mining, portfolio optimization, and strategy backtesting.

Language Options

🇨🇳 中文 (Chinese) - README_ZH.md
🇯🇵 日本語 (Japanese) - README_JP.md

Core Value Proposition

Value Pillar	Description
🎯 Complete Factor Lifecycle Management	Full support from factor creation, validation, analysis to deployment
🧪 Scientific Factor Evaluation System	Professional indicators including IC/IR analysis, monotonicity test, turnover analysis
🧬 Intelligent Factor Mining	Genetic algorithm-based automated factor mining to discover alpha signals
📊 Professional Backtesting Engine	Support for multi-factor combination, strategy comparison, and performance attribution analysis

Core Features

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1. Factor Management

✅ Custom Factor Definition - Supports Tongda Xinhua (MyLanguage) syntax and TALib functions
✅ Formula Validation - Real-time syntax checking and logical verification
✅ Version Control - Factor modification history and version rollback
✅ Pre-built Factor Library - Built-in common technical factors (MA, RSI, MACD, Bollinger Bands, etc.)

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2. Factor Analysis

✅ IC/IR Analysis - Information Coefficient and Information Ratio calculation (supports 1-day, 5-day, 10-day prediction cycles)
✅ Factor Exposure Analysis - Analyze stock exposure distribution on factors
✅ Factor Effectiveness Testing - Multi-dimensional assessment of factor predictive power
✅ Factor Attribution Analysis - Decompose factor contribution to returns
✅ Dynamic Monitoring - Factor performance tracking across time series dimensions

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3. Factor Mining

✅ Genetic Algorithm Mining - DEAP-based evolutionary algorithm for automatic factor search
✅ Multi-objective Optimization - Simultaneously optimize IC, IR, monotonicity, and other objectives
✅ Factor Generation - Supports basic operators, function calls, and time window operations
✅ Parallel Computing - Parallel population evaluation for acceleration

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4. Portfolio Analysis

✅ Multi-factor Portfolio - Supports equal weight, market cap weighting, IC_IR maximization, etc.
✅ Risk Modeling - Factor neutralization processing
✅ Optimization Configuration - Factor weight optimization based on historical performance
✅ Portfolio Performance - Annual return, Sharpe ratio, maximum drawdown, and other metrics

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5. Strategy Backtesting

✅ Single Factor Backtesting - Factor quantile-based stock selection backtesting
✅ Multi-factor Strategies - Composite factor signal generation
✅ Strategy Comparison - Multi-strategy parallel backtesting and comparison analysis
✅ Performance Metrics - Complete metric system including returns, risk, and turnover
✅ Visualization Charts - Equity curves, drawdowns, factor performance charts, etc.

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Technical Architecture

Tech Stack

Backend:

FastAPI 0.135+ - High-performance web framework
SQLAlchemy 2.0 - ORM database operations
SQLite - Lightweight data storage
Pandas 2.0+ / NumPy - Data processing
TA-Lib - Technical analysis library
VectorBT 0.25+ - Backtesting engine
DEAP 1.3+ - Genetic algorithm framework
XGBoost 2.0+ - Machine learning models
SHAP 0.42+ - Model interpretation
akshare 1.12+ - Chinese A-share data source

Frontend:

React 19 - UI framework
TypeScript - Type safety
Ant Design 6 - UI component library
ECharts 6 - Data visualization
React Router 7 - Routing management
Axios - HTTP client
Vite - Build tool

Project Structure

FactorHub/
├── backend/                    # Backend code
│   ├── api/                   # API layer
│   │   ├── main.py           # FastAPI main application
│   │   └── routers/          # API routers
│   │       ├── factors.py    # Factor management interface
│   │       ├── analysis.py   # Factor analysis interface
│   │       ├── mining.py     # Factor mining interface
│   │       ├── portfolio.py  # Portfolio analysis interface
│   │       ├── backtest.py   # Strategy backtesting interface
│   │       └── data.py       # Data management interface
│   ├── services/              # Business logic layer
│   ├── strategies/            # Strategy implementation
│   ├── repositories/          # Data access layer
│   ├── models/                # ORM models
│   └── core/                  # Core configuration
├── frontend/                   # Frontend code
│   └── react-antd/            # React + Ant Design version
├── config/                     # Configuration files
├── data/                       # Data directory
├── docs/                       # Documentation
├── tests/                      # Tests
├── scripts/                    # Utility scripts
└── README.md

Quick Start

Prerequisites

Python 3.11+
Node.js 18+
pnpm (package manager)
TA-Lib (technical analysis library)

Installation

# Install pnpm
npm install -g pnpm

# Install Python dependencies (using uv)
uv sync

# Install frontend dependencies
cd frontend/react-antd
pnpm install

One-click Startup

python start_all.py

This script will automatically:

Check environment prerequisites
Install dependencies if needed
Start backend service (http://localhost:8000)
Start frontend development server (http://localhost:5173)
Open browser automatically

Manual Startup

Backend

uv run python start_api.py
# API available at http://localhost:8000
# API docs at http://localhost:8000/docs

Frontend

cd frontend/react-antd
pnpm dev
# Frontend available at http://localhost:5173

License

Dual License

Personal Use:

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

You are free to:

✅ Use this software for personal learning, research, and non-commercial purposes
✅ Modify and improve this software
✅ Distribute modified versions (must retain the same license)
✅ Reference this project in your own projects

Commercial Use:

⚠️ Important Note: Any commercial use (including but not limited to:

Integrating this project into commercial products
Using this project to provide paid services
Using this project for production quantitative trading
Using this project internally within companies for investment research)

Requires separate commercial authorization.

Contact for Commercial Authorization

Email: yl_zhangqiang@foxmail.com

When contacting, please specify:

Your company/organization name
Your usage scenario and requirements
Expected scale of use
Contact information

We will respond within 3 business days.

Contact

Project Maintainer: FactorHub Team