Analysis updated 2026-07-03 · repo last pushed 2026-07-03
Screen all Chinese A-share stocks using 18 built-in strategies or your own custom signals.
Backtest trading strategies against historical data with realistic fees and slippage costs.
Set up real-time market monitoring with alerts sent to Feishu when conditions are met.
Connect an AI language model to generate trading strategies or automated market reviews.
| shy3130/tickflow-stock-panel | tigicion/dao-code | bookorbit/bookorbit | |
|---|---|---|---|
| Stars | 1,368 | 1,368 | 1,344 |
| Language | TypeScript | TypeScript | TypeScript |
| Last pushed | 2026-07-03 | 2026-07-01 | 2026-07-03 |
| Maintenance | Active | Active | Active |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 2/5 | 4/5 |
| Audience | developer | developer | general |
Figures from each repo's GitHub metadata at analysis time.
Requires deploying a self-contained Docker container and connecting it to a TickFlow data source to pull market data into local storage.
TickFlow Stock Panel is a self-hosted workspace for individual investors and quantitative trading enthusiasts focused on Chinese A-share markets. It brings stock screening, portfolio monitoring, and backtesting together in one dashboard. You run it on your own machine, connect it to a data source called TickFlow, and get a personal quantitative research station without needing to manage complex infrastructure. The tool works by pulling market data from TickFlow into local storage, then letting you act on it through several connected modules. You can scan all A-share stocks using 18 built-in strategies or your own custom signals. A backtesting engine lets you simulate how those strategies would have performed in the past, factoring in real-world trading costs like fees, slippage, and daily settlement rules. The monitoring center watches the market in real time and can send you alerts through Feishu (a messaging platform) when your specified conditions are met. The project also integrates optional AI capabilities, meaning you can connect a large language model to generate trading strategies or produce automated market reviews. This project is built for individual retail investors and hobbyist quant researchers who want professional-grade tools without relying on commercial software. For example, a retail trader could use it to screen the entire A-share market for stocks matching specific technical patterns, backtest a moving average strategy over the past year, and set up real-time alerts for when certain stocks hit target price levels. It also appeals to users who want deeper analysis, offering tools to track consecutive limit-up stocks, analyze financial statements, and review concept sector rotations. A notable design choice is the project's clear boundary on what it does not do. The developer explicitly states it will not try to compete with established retail platforms like Tongdaxin or THS, and it does not build in AI features that recommend specific stocks or predict daily limit-ups. It is strictly a research and analysis tool. The codebase relies on fast data-processing libraries to handle market-wide scans in milliseconds, and it is designed to deploy as a single, self-contained container.
A self-hosted dashboard for Chinese A-share stock screening, backtesting, and real-time monitoring. Connect it to a TickFlow data source to run your own quantitative trading research without commercial software.
Mainly TypeScript. The stack also includes TypeScript, Docker, TickFlow.
Active — commit in last 30 days (last push 2026-07-03).
The explanation does not mention a specific license, so the licensing terms are unknown.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.