# thuquant/awesome-quant

中国的Quant相关资源索引

Repository: https://github.com/thuquant/awesome-quant
Canonical: https://ross.abutalabs.com/products/thuquant-awesome-quant
License: MIT
License Family: permissive
Topics: quant, python, machine-learning, statistics, r, cpp, trading, finance, china
Last push: 2026-08-24T05:35:24+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 3767, "days_push": 9, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5579, forks 1016 (observed 2026-08-28T04:09:22.537271+00:00)

## What it is
A curated Chinese-language awesome-list indexing quantitative finance resources, covering data sources, databases, trading platforms, backtesting frameworks, trading APIs, and programming materials for Python, R, C++, and Julia. It focuses on China's quant ecosystem (A-shares, domestic data vendors) while also including international tools and references.

## Use cases
- find free market data APIs for Chinese A-share stocks
- discover backtesting frameworks for quant trading strategies
- learn quantitative finance with books and papers in Chinese
- compare China quant trading platforms and broker APIs
- find time-series databases for tick data
- locate Python libraries for financial data analysis

## When to choose
- you work with Chinese financial markets and need localized data sources and platforms
- you want a starting point to explore the quant ecosystem across languages
- you need an up-to-date index of trading, backtesting, and data tools

## When to avoid
- you need executable software rather than a link collection
- you need deep non-China-focused coverage without additional research
- you expect documentation or tutorials rather than curated links

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: fintech, machine-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, quantitative-finance, china-markets, trading, backtesting, curated-resources

## Member repositories
- thuquant/awesome-quant (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:22.537271+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:55:33.980103+00:00, confidence not recorded.
  - readme: https://github.com/thuquant/awesome-quant (fetched 2026-08-28T04:09:22.537271+00:00, sha 0ca417304471)
- Data as of 2026-08-30T08:39:29.467469+00:00.