A powerful skill for retrieving and managing high-quality Chinese A-share investment data for quantitative analysis and financial modeling.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install investment-data
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 investment-data 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 investment-data?
The investment-data skill provides a comprehensive toolkit for developers and quant researchers to access high-quality Chinese A-share market data. By leveraging the investment_data project, this skill automates the retrieval of daily closing prices, limit up/down statistics, and index weights, ensuring your financial models are backed by verified, multi-source information.
Integrated seamlessly into your workflow, this Openclaw Skills contribution supports various output formats including CSV, JSON, and Qlib. It is designed for reliability, featuring automated daily updates and the inclusion of delisted stock data to prevent survivorship bias in backtesting.
investment-data Use Cases
- Building quantitative trading strategies for the Chinese A-share market.
- Backtesting financial models with high-quality historical OHLCV and adjusted price data.
- Monitoring market-wide indices and individual stock limit up/down statuses.
- Researching delisted companies to avoid survivorship bias in data analysis.
- Automating financial data pipelines with daily T+1 updates using Openclaw Skills.
How investment-data Works
- The skill initializes by checking for system dependencies like Python 3 and wget.
- Users download the latest verified dataset from remote repositories such as GitHub or DoltHub.
- The DataClient interface allows for precise queries of specific stocks or indices via Python or CLI tools.
- Optional Tushare tokens can be configured for real-time data delta updates.
- Automated cron tasks within the Openclaw Skills framework ensure the local data directory remains current every morning.
investment-data Setup
To set up this skill, ensure you have the required system binaries like python3 and wget. Install the necessary Python dependencies using the following commands:
pip install pandas numpy requests
Configure your storage path and optional Tushare token for real-time updates:
export INVESTMENT_DATA_DIR=~/.qlib/qlib_data/cn_data
export TUSHARE_TOKEN=your_token_here
Download the initial dataset to get started:
python scripts/download_data.py --latest
investment-data Data Schema & Taxonomy
The skill organizes data into a structured directory optimized for the Qlib format or standard exports.
| Data Type | Description | Formats |
|---|---|---|
| Daily Price | OHLCV, Volume, Amount | CSV, JSON, Qlib |
| Limit Data | Price limits and status | CSV, JSON |
| Index Data | Weights and constituents | CSV |
| Adjusted Data | Pre-adjusted and post-adjusted prices | CSV, Qlib |
investment-data Advanced Features
- Multi-source cross-verification to ensure data integrity and automatically fix anomalies.
- Full support for delisted stocks to facilitate professional-grade backtesting without survivorship bias.
- Native Openclaw Skills integration for scheduled daily updates via cron tasks.
- Batch processing scripts for exporting massive datasets to Excel, JSON, or CSV formats.
- Flexible configuration via config.yaml for prioritizing data sources like Tushare, AkShare, or Yahoo Finance.
SKILL.md
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