FinHackCN/finhack
FinHack®，一个易于拓展的量化金融框架，它在当前版本中集成了数据采集、因子计算、因子挖掘、因子分析、机器学习、策略编写、量化回测、实盘接入等全流程的量化投研工作。 observed · 2026-08-28
Health v2 · maintenance only
76/100
- Activity 98
- Release rhythm 35
- Longevity 98
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1382
- days_rel: n/a
- days_push: 14
- n_releases_24m: 0
Adoption not part of the score
1145 stars · 224 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
FinHack is an extensible Python quantitative finance framework covering the full quant research workflow: data collection, factor computation and mining, factor analysis, machine learning, strategy development, backtesting, and live trading integration. It includes an Alpha101/Alpha191 formula-based factor engine, A-share backtesting rules (price limits, T+1), dynamic adjustment mechanisms, and multiprocess backtesting and model training.
Use cases
- backtest A-share trading strategies with T+1 and price limit rules
- compute Alpha101 and Alpha191 factors from a formula engine
- mine and analyze stock factors with machine learning
- collect market data from tushare into MySQL
- run multiprocess backtests and model training on a server
- connect strategies to live trading
- organize multiple strategy projects with isolated environments
When to choose
- you need an end-to-end open-source quant research pipeline for Chinese A-share markets
- you want extensible factor computation, mining, and backtesting in Python
- you need multiprocess backtesting and ML training on your own hardware
When to avoid
- you need US stocks, futures, forex, or crypto support (planned but not implemented)
- you require a stable, production-ready system - the project is mid-refactor and currently broken
- you need Windows support or a lightweight install without MySQL/Redis
- you cannot accept the GPL-3.0 dual license for commercial use
Facets
framework · maturity experimental
machine-learning data-science etl caching database workflow-automation trading fintech machine-learning python cli quantitative-finance backtesting factor-mining alpha-factors tushare a-share live-trading quant-research mysql redis data-engineering automation linux docker
2 sources
- readme: https://github.com/FinHackCN/finhack · fetched 2026-08-28 · 36f17883dfb1
- homepage: https://github.com/FinHackCN/finhack/wiki/1%E3%80%81%E5%BF%AB%E9%80%9F%E5%85%A5%E9%97%A8 · fetched 2026-08-29 · bb13a04cf85a
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| FinHackCN/finhack | main | 76 |
For agents
markdown · JSON · MCP: product_card(name="FinHackCN/finhack")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem