A comprehensive quantitative analysis suite providing real-time global market data and multi-dimensional AI scoring for stocks and commodities.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install trading-quant
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 trading-quant 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 Trading Quant Analysis Tool?
The Trading Quant tool is a sophisticated quantitative analysis engine designed for the Openclaw Skills ecosystem. It integrates real-time data feeds from major providers like Tencent, Sina, and East Money to offer a deep dive into A-shares, US stocks, Hong Kong stocks, and precious metals. By combining traditional technical indicators with modern LLM-driven sentiment analysis, it provides a holistic view of market conditions.
This skill is particularly valuable for traders who need a unified interface to monitor capital flows, technical signals, and fundamental valuations simultaneously. As part of the Openclaw Skills library, it ensures that your AI coding agent has access to live financial truths rather than relying on outdated training data.
Trading Quant Analysis Tool Use Cases
- Real-time price tracking and multi-dimensional scoring for global equities.
- Monitoring Northbound capital flow and main force money movements.
- Identifying market anomalies such as limit up/down stocks and unusual volume spikes.
- Conducting technical analysis using MACD, RSI, and KDJ indicators.
- Evaluating market sentiment and news impact through integrated LLM analysis.
How Trading Quant Analysis Tool Works
- The user triggers a specific analysis command via the CLI, targeting a stock code or market segment.
- The system fetches live data from primary sources (e.g., Tencent), with built-in failover to secondary sources like Sina or East Money.
- A 5-dimension evaluation algorithm processes the data, weighing Technicals (25%), Capital Flow (30%), Fundamentals (10%), News (20%), and Sentiment (15%).
- For news and sentiment, the skill leverages LLM capabilities to parse raw text and market data into quantitative scores.
- The tool outputs a standardized signal ranging from STRONG_BUY to STRONG_SELL, accompanied by risk warnings for extreme valuations.
Trading Quant Analysis Tool Setup
To integrate this quantitative capability into your Openclaw Skills environment, ensure you have Python 3.12 installed and run the following command structure:
# Analyze specific A-share stocks
python3.12 scripts/quant.py stock_analysis [codes]
# Get a global market overview
python3.12 scripts/quant.py global_overview
Trading Quant Analysis Tool Data Schema & Taxonomy
The skill organizes market data into a structured scoring matrix to ensure consistent evaluation across different Openclaw Skills workflows:
| Dimension | Indicators Included |
|---|---|
| Technical | MACD, RSI, KDJ, Moving Averages, Bollinger Bands |
| Capital | Volume Ratio, Turnover Rate, Main Force Flow, Price-Volume Dynamics |
| Fundamental | PE Ratio, PB Ratio, Total Market Capitalization |
| News | LLM-processed news sentiment scoring |
| Sentiment | LLM-processed overall market atmosphere evaluation |
Trading Quant Analysis Tool Advanced Features
- Intelligent failover chain: Automatically switches data sources (Tencent -> Sina -> East Money) to ensure high availability.
- Real-time Northbound flow monitoring for tracking foreign institutional movements in A-shares.
- Automated K-line 'warming' and daily data persistence for offline analysis.
- Risk alert system for extreme PE (>100) or PB (<0.8) values to prevent high-risk entries.
- Support for global commodities and precious metals including real-time gold analysis.
SKILL.md
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