# ZhuLinsen/daily_stock_analysis

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。  LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.

Repository: https://github.com/ZhuLinsen/daily_stock_analysis
Canonical: https://ross.abutalabs.com/products/daily_stock_analysis
Homepage: https://dsa.zhulinsen.tech
Language: Python
License: MIT
License Family: permissive
Topics: aigc, llm, quant, quantitative-trading, a-stock, ai-agent, quantitative-finance
Last push: 2026-08-25T14:54:01+00:00

## Health v2 (maintenance only)
Score: 82/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 99, longevity 16
- inputs: {"age_days": 235, "days_push": 8, "days_rel": 10, "gap_med": 4.0, "n_releases_24m": 35}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 64010, forks 53727 (observed 2026-08-28T04:12:19.187700+00:00)

## What it is
An LLM-powered stock analysis application that aggregates multi-source market data, news, and fundamentals for A-share, HK, US, Japanese, Korean, and Taiwanese markets, generating daily AI decision reports with scores, trends, and risk alerts. It includes a FastAPI/WebUI workbench, agent-based strategy Q&A, backtesting, and automated push to WeChat Work, Feishu, Telegram, Discord, Slack, and email, with zero-cost scheduled runs via GitHub Actions.

## Use cases
- analyze my watchlist stocks daily with AI and push a report
- generate LLM stock decision reports for A-shares and US stocks
- get daily market review and stock analysis on Telegram or Feishu
- run scheduled stock analysis without a server using GitHub Actions
- ask an AI agent strategy questions about a specific stock
- aggregate stock quotes, news, and fundamentals from multiple data sources
- backtest past AI stock reports and track accuracy
- self-host a stock analysis dashboard with Docker

## When to choose
- you want automated daily AI-generated stock research reports pushed to chat or email
- you track stocks across Chinese, Hong Kong, and US markets and want multi-source data with fallbacks
- you want a zero-cost scheduled setup via GitHub Actions or a self-hosted Docker deployment
- you need a web workbench with history, backtesting, and strategy Q&A around your watchlist

## When to avoid
- you need high-frequency or algorithmic trade execution rather than daily research reports
- you require guaranteed real-time market data feeds with strict SLAs
- you want a fully deterministic quant backtesting engine without LLM involvement
- you cannot provide any LLM API key or prefer not to send financial data to cloud AI services

## Facets
- artifact type: application
- maturity: active
- function: llm-inference, agent-framework, data-visualization, analytics, web-scraping, workflow-automation, scheduling, webhook, chatbot
- domain: fintech, artificial-intelligence, large-language-models, data-science, self-hosted, analytics
- platform: python, cli, self-hosted, cross-platform
- tags: stock-analysis, quantitative-finance, a-stock, watchlist, market-data, decision-dashboard, github-actions, fastapi, news-sentiment, backtesting, notifications, trading, ai-agents, automation, docker, web-server

## Member repositories
- ZhuLinsen/daily_stock_analysis (main) score 82

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:19.187700+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 2026-08-29T16:17:25.994487+00:00, confidence not recorded.
  - readme: https://github.com/ZhuLinsen/daily_stock_analysis (fetched 2026-08-28T04:12:19.187700+00:00, sha 2a3babba226e)
  - homepage: https://dsa.zhulinsen.tech (fetched 2026-08-28T17:55:56.810151+00:00, sha 56d13ef3c2e3)
  - site_page: https://dsa.zhulinsen.tech/docs/ (fetched 2026-08-28T17:55:56.819056+00:00, sha d3b19f45a89a)
  - site_page: https://dsa.zhulinsen.tech/docs/quick-start/ (fetched 2026-08-28T17:55:56.821049+00:00, sha d77c54e2120c)
  - site_page: https://dsa.zhulinsen.tech/docs/github-actions/ (fetched 2026-08-28T17:55:56.822626+00:00, sha 3dd901509bdf)
  - site_page: https://dsa.zhulinsen.tech/docs/local/ (fetched 2026-08-28T17:55:56.824203+00:00, sha ab470bdc5e5a)
  - site_page: https://dsa.zhulinsen.tech/docs/docker/ (fetched 2026-08-28T17:55:56.825662+00:00, sha 936144fae9d0)
- Data as of 2026-08-30T08:39:29.467469+00:00.