# ScottZt/jin-ce-zhi-suan

【金策智算】➡️不靠情绪买卖、不追小道消息，专注用客观数据辅助决策。 我们仅提供本地化私有行情数据服务与历史回测工具，帮你把主观想法变成可验证的交易规则，用历史数据检验方法有效性，通过指标监控约束随意操作、控制回撤风险，让交易更有纪律、更落地。 本产品为纯量化工具，不荐股、不指导买卖、不预测行情、不承诺收益，所有决策由用户自主判断，只为你提供客观的数据支撑与AI辅助。作者【硅基流码】

Repository: https://github.com/ScottZt/jin-ce-zhi-suan
Canonical: https://ross.abutalabs.com/products/jin-ce-zhi-suan
Language: HTML
License: NOASSERTION
License Family: other
Last push: 2026-07-20T04:32:48+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 93, release rhythm 90, longevity 11
- inputs: {"age_days": 163, "days_push": 44, "days_rel": 67, "gap_med": 7.5, "n_releases_24m": 7}
- flags: young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1466, forks 435 (observed 2026-08-28T04:04:48.370547+00:00)

## What it is
A self-hosted quantitative trading research and backtesting system for Chinese A-share markets, built with Python and FastAPI with a web dashboard. It decouples strategy generation, risk-control review, and execution into a layered 'Three Departments and Six Ministries' architecture, and supports natural-language stock screening via LLMs.

## Use cases
- backtest trading strategies on historical A-share data
- convert natural language stock screening ideas into executable rules
- manage multiple trading strategies with risk controls
- convert TDX formulas and parse BLK sector pools
- run strategy evolution and performance comparison
- monitor drawdown and enforce position limits
- batch backtest a portfolio of stocks

## When to choose
- you trade Chinese A-share markets and want a local, private backtesting tool
- you want to turn plain-language strategy ideas into testable rules with LLM assistance
- you need built-in risk controls like stop-loss, drawdown limits, and position constraints
- you want a web dashboard to configure and run backtests without writing code

## When to avoid
- you need live trading execution or broker integration - this is backtesting and analysis only
- you trade non-Chinese markets or need global market data sources
- you expect stock picks, predictions, or guaranteed returns - the tool explicitly provides none
- you require a permissively licensed library to embed in your own product - the license is non-standard

## Facets
- artifact type: application
- maturity: active
- function: trading, data-visualization, web-framework, machine-learning, llm-inference, analytics, benchmarking
- domain: fintech, data-science, analytics, large-language-models, self-hosted
- platform: python, self-hosted, cross-platform
- tags: quantitative-trading, backtesting, a-share, stock-screening, risk-control, fastapi, trading-strategy, chinese-stock-market, ai-stock-picking, dashboard, web-server

## Member repositories
- ScottZt/jin-ce-zhi-suan (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:48.370547+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 2026-08-30T04:35:02.610892+00:00, confidence not recorded.
  - readme: https://github.com/ScottZt/jin-ce-zhi-suan (fetched 2026-08-28T04:04:48.370547+00:00, sha 0fc8c03f93d7)
- Data as of 2026-08-30T08:39:29.467469+00:00.