A professional-grade quantitative trading system for cryptocurrency that handles everything from backtesting and strategy optimization to live execution.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quant-trader
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 quant-trader 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 Quant Trader?
The Quant Trader skill is a robust toolkit designed for developers and traders who want to build, test, and deploy algorithmic trading strategies in the cryptocurrency market. By leveraging Openclaw Skills, this tool provides a seamless bridge between strategy development and execution, supporting over 100 exchanges via the ccxt library. It empowers users to move beyond manual trading by providing an event-driven framework for backtesting historical data, simulating real-time markets through paper trading, and executing live orders with built-in risk management protocols.
Quant Trader Use Cases
- Developing and backtesting new technical analysis strategies such as Moving Average crossovers or RSI Mean Reversion.
- Optimizing strategy parameters using Bayesian methods to maximize the Sharpe ratio or total return.
- Transitioning from historical testing to real-time paper trading without changing the underlying code.
- Automating live trading on exchanges like Binance and OKX with strict risk management controls.
- Analyzing portfolio performance with professional metrics like Max Drawdown, Sortino Ratio, and Win Rate.
How Quant Trader Works
- Strategy Definition: Users define a strategy by inheriting from the base Strategy class and implementing custom initialization and logic methods.
- Data Fetching: The skill retrieves historical or real-time OHLCV data from exchange APIs, CSV files, or local databases.
- Backtesting: The engine runs the strategy against historical data to generate detailed performance reports and visualizations.
- Optimization: The system runs multiple iterations using advanced optimization algorithms to find the best parameter combinations.
- Execution: The user selects between paper trading for simulation or live trading for real execution to deploy the strategy to the market.
Quant Trader Setup
To get started with this skill, follow these installation steps:
clawhub install quant-trader
Clone the core repository and install the Python dependencies:
git clone https://github.com/ZhenRobotics/openclaw-quant.git ~/openclaw-quant
cd ~/openclaw-quant
pip install -r requirements.txt
Configure your environment variables for live exchange access:
export BINANCE_API_KEY="your-key"
export BINANCE_API_SECRET="your-secret"
Quant Trader Data Schema & Taxonomy
The skill organizes trading data and results through a structured object model:
| Component | Format | Description |
|---|---|---|
| Market Data | Pandas DataFrame | Contains Open, High, Low, Close, and Volume columns. |
| Strategy Class | Python Object | Encapsulates trading logic, indicators, and parameters. |
| Backtest Result | JSON/Object | Includes performance metrics like Sharpe and Drawdown. |
| Config File | YAML | Manages exchange credentials, risk limits, and notifications. |
| Indicators | Vectorized Arrays | Calculated using the internal indicator engine for speed. |
Quant Trader Advanced Features
- Bayesian Optimization: Automated parameter tuning using Optuna to find mathematically optimal trading settings.
- Multi-Exchange Broker: A unified interface to interact with over 100 cryptocurrency exchanges simultaneously via ccxt.
- Risk Management Hook: Built-in position sizing and automatic stop-loss/take-profit management based on real-time account equity.
- Vectorized Indicators: High-performance calculation for over 50 technical indicators including MACD, Bollinger Bands, and VWAP.
- Custom Notifications: Real-time alerts via Telegram for order execution and significant market events within Openclaw Skills workflows.
SKILL.md
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