A professional-grade stock screening engine implementing the Yang Yongxing closing-bell strategy for real-time market analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install yang-selection
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install yang-selection using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Yang Selection Stock Strategy?
This Openclaw Skills module implements the renowned Yang Yongxing closing-bell stock selection strategy, designed to identify high-momentum equities in the Chinese market. It utilizes a sophisticated two-step filtering process that combines real-time price action from Tencent Finance with deep historical technical analysis from Baostock. This Openclaw Skills tool is optimized for developers and traders who need high-performance screening without the overhead of complex proprietary platforms.
The tool focuses on stocks with specific market capitalizations and turnover rates, ensuring liquidity and volatility profiles suitable for the strategy. By incorporating an intelligent local cache for market cap data, it significantly reduces API latency and prevents redundant network requests, making it a robust solution for daily trading workflows.
Yang Selection Stock Strategy Use Cases
- Daily screening for end-of-day (closing-bell) buy signals in the A-share market.
- Automated filtering of stocks based on specific turnover and market capitalization windows.
- Technical analysis automation to identify stocks with price-volume breakouts and moving average alignment.
How Yang Selection Stock Strategy Works
- The skill first retrieves a comprehensive list of main board stocks using the query-main-board-stocks dependency.
- It performs a basic screen via the Tencent Finance API, filtering for stocks with a 3% to 5% price increase and 5% to 10% turnover.
- The system checks market capitalization against a local cache or the live API, ensuring candidates fall between 5 billion and 20 billion RMB.
- Candidates passing the first round undergo deep screening via Baostock to verify volume ratios and five-day volume growth.
- Technical indicators are analyzed to ensure 5/10/20-day moving averages are positioned above the 60-day moving average and the price has reached a daily high.
- The final list of matching stocks is output directly to the terminal for immediate action.
Yang Selection Stock Strategy Setup
To integrate this tool into your Openclaw Skills environment, install the necessary Python dependencies and run the initialization scripts:
pip install baostock pandas numpy requests
# First, generate the main board stock list
python3 query_main_board_stocks.py
# Run the selection strategy
python3 yang_selection.py
Yang Selection Stock Strategy Data Schema & Taxonomy
| File/Source | Type | Description |
|---|---|---|
market_cap_cache.json |
Local Cache | Stores market capitalization data for 30 days to optimize performance. |
query-main-board-stocks |
Dependency | External skill providing the initial stock universe. |
| Tencent Finance | API | Real-time行情 (Real-time market quotes) and turnover data. |
| Baostock | API | Historical technical data and volume analysis. |
Yang Selection Stock Strategy Advanced Features
- Intelligent caching mechanism with a 30-day TTL (Time-To-Live) for market cap data to maximize efficiency.
- Built-in rate limiting set at 10 stocks per second to prevent API blocking and ensure stability.
- Two-tier screening logic that separates light real-time checks from heavy historical data processing.
- Seamless integration with other Openclaw Skills for modular trading pipeline construction.
SKILL.md
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