An automated quantitative trading integration for Longbridge Securities featuring oversold and momentum strategies with real-time Feishu notifications.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install longport-quant-trader
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install longport-quant-trader using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Longport Quant Trader is a robust quantitative trading skill designed for individual investors and quant enthusiasts looking to automate their activity in the Hong Kong and US stock markets. By integrating directly with Longbridge Securities, this skill enables a high degree of automation, scanning the market every 5 minutes to execute predefined strategies without manual intervention. It serves as a bridge between complex market data and actionable execution, providing a professional-grade trading environment for Openclaw Skills users.
The skill focuses on two primary market conditions: catching oversold rebounds and riding momentum trends. With built-in risk management tools like automated take-profit and stop-loss orders, it ensures that your capital is protected while you sleep. Beyond execution, it provides comprehensive performance tracking and real-time reporting through Feishu, keeping you informed of your portfolio's health at all times.
Ensure you have Python 3.12 installed on your system.
First, install the required dependencies using pip:
pip install longport python-dotenv
Obtain your API credentials from Longbridge Open Platform and set up your environment variables:
export LONGPORT_APP_KEY="your_app_key"
export LONGPORT_APP_SECRET="your_app_secret"
export LONGPORT_ACCESS_TOKEN="your_access_token"
Launch the monitoring script to begin automated trading with Openclaw Skills:
python quant_monitor.py
The skill manages trading data through a structured configuration and reporting system:
| Data Component | Format | Description |
|---|---|---|
| Strategy Parameters | Python/Config | Defines thresholds for momentum, reversion, and risk levels. |
| Performance Stats | JSON/CLI | Tracks win rate, total profit/loss, and drawdown metrics. |
| Position Log | CLI Table | Real-time display of current holdings, entry prices, and floating P/L. |
| Notifications | Feishu Webhook | Outbound JSON payloads containing trade execution and performance reports. |
| Stock Pool | List | Custom list of ticker symbols (e.g., 700.HK, 9988.HK) for monitoring. |
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