Self-hosted AI stock monitor for A-shares, Hong Kong and US stocks, with portfolio tracking, price alerts, TradingAgents-based analysis and automated reports.
2.1K401PythonMITUpdated yesterday
jundizhou/easy-stock
A-share (China stock market) AI research workstation for market analysis, theme tracking, stock research, portfolio inspection and post-market review, local-first desktop app.
Open-source alternative to:Wind
Tonghuashun (iFinD)
- Stars
- 1,544
- Forks
- 154
- Open issues
- 3
- Last commit
- yesterday
What is it?
easy-stock is a desktop research workstation for China's A-share market. It aggregates quote, K-line, theme, limit-up and news data from several public sources, then organizes trend, sector, consecutive-limit-up ladder and sentiment history into structured views that an AI assistant can interpret.
The app covers a daily workflow: market overview, theme radar, short-term limit-up analysis, tiered single-stock research (quick quant screen or AI reports at several depths), and portfolio inspection with a weighted four-dimension score. It can also collect posts from famous market commentators on Xueqiu and Taoguba, clean the text, archive it locally, and generate cross-author consensus and disagreement summaries on a schedule.
The backend is written in Go with a React and TypeScript frontend inside an Electron shell. Data and research records are stored in local SQLite. AI runs through either Hermes or Codex runtimes, with support for several model providers. The project is source-available under a non-commercial license.
Key features
- 01Aggregates A-share quotes, K-lines, themes, limit-up pools and news from multiple sources.
- 02Tracks theme radar, sector capital flows and consecutive-limit-up ladders.
- 03Runs tiered single-stock research from a quant screen to deep AI analysis.
- 04Inspects multi-stock portfolios with a weighted score and reuses recent stock reports.
- 05Schedules automatic collection and summarization of commentator posts on Xueqiu and Taoguba.
- 06Stores articles, research and sessions locally, with data source and timestamp shown.
Use cases
- Reviewing each trading day's limit-up structure and sentiment after market close.
- Following multiple market commentators' views and their next-day predictions in one place.
- Running structured AI research on a watchlist or existing holdings.
- Checking a portfolio's concentration and risk against a chosen trading style.
Quick start
- 1
Download the latest desktop installer from GitHub Releases
- 2
Read the user guide to configure an LLM and log in to Xueqiu and Taoguba
- 3
For running from source, read the developer documentation
Things to know
- Licensed under PolyForm Noncommercial 1.0.0, so commercial use requires a separate license from the author.
- Focused on the A-share (China) market and relies on Chinese data sources and platforms.
- Some AI features need your own model API key, and Codex requires a Responses-compatible model connection.
Topics
FAQ
- What is easy-stock?
- A-share (China stock market) AI research workstation for market analysis, theme tracking, stock research, portfolio inspection and post-market review, local-first desktop app. easy-stock is a desktop research workstation for China's A-share market. It aggregates quote, K-line, theme, limit-up and news data from several public sources, then organizes trend, sector, consecutive-limit-up ladder and sentiment history into structured views that an AI assistant can interpret.
- Is easy-stock free to use? What license does it have?
- easy-stock is open source under the Other license. Check the license terms before using it in commercial products.
- Is easy-stock still maintained?
- Actively maintained. The last commit to easy-stock was on Oct 19, 2026.
- What can I use easy-stock for?
- Reviewing each trading day's limit-up structure and sentiment after market close. Following multiple market commentators' views and their next-day predictions in one place. Running structured AI research on a watchlist or existing holdings. Checking a portfolio's concentration and risk against a chosen trading style.
- How do I install easy-stock?
- Download the latest desktop installer from GitHub Releases Read the user guide to configure an LLM and log in to Xueqiu and Taoguba For running from source, read the developer documentation
- Where can I get easy-stock?
- The source code and installation instructions are on GitHub: https://github.com/jundizhou/easy-stock
Summary generated by AI from the project's README. GitHub stats refresh daily.
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