A professional framework for developing, testing, and deploying quantitative trading strategies with strict consistency between backtesting and live execution.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quant-strategy-dev
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-strategy-dev 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 Strategy Dev?
Quant Strategy Dev is a specialized tool within the Openclaw Skills ecosystem designed for quantitative researchers and algorithmic traders. It provides a standardized development lifecycle for trading strategies, covering everything from initial logic design to small-scale live production. By enforcing strict code consistency between backtesting engines and live trading environments, it minimizes the risk of 'model drift' and execution errors.
The skill integrates deeply with the QMT (Quantitative Management Terminal) environment, offering pre-configured code templates, robust risk management protocols, and comprehensive testing suites. It ensures that every trade is backed by rigorous validation, helping developers maintain high code quality and financial safety in volatile markets.
Quant Strategy Dev Use Cases
- Designing and implementing quantitative trading strategies for A-shares and US stocks.
- Creating automated stop-loss and take-profit mechanisms for algorithmic portfolios.
- Bridging the gap between historical backtesting and live market execution using identical logic.
- Implementing risk-controlled order execution (e.g., prType=14) to manage slippage.
- Scaling trading operations from small-capital testing to full-scale production.
How Quant Strategy Dev Works
- Strategy Design: Define clear, quantifiable buy/sell signals, capital management rules, and risk control parameters.
- Code Development: Utilize standardized Python templates featuring Global State objects and order deduplication (waiting_list).
- Modular Testing: Execute mandatory unit tests and boundary case validations to ensure functional integrity before deployment.
- Backtest Verification: Validate the strategy against historical data using parameters identical to the live environment.
- Risk Review: Conduct a final audit of signal ranges, order types, and funding limits.
- Live Incubation: Launch with small capital (5000-10000 CNY) for a 1-2 week observation period to monitor execution stability.
Quant Strategy Dev Setup
To initialize the development environment for Openclaw Skills quant development, ensure you have the QMT environment ready and use the following structure:
# Initialize your quant project directory
mkdir -p quant-project/tests
# Install required dependencies (example for QMT-compatible libs)
pip install pandas numpy qmt-api-mock
# Create your strategy file based on the provided template
touch strategy_main.py
Quant Strategy Dev Data Schema & Taxonomy
The skill organizes trading data and metadata through a structured taxonomy to ensure transparency:
| Data Component | Description | Format |
|---|---|---|
| Global State (G) | Manages real-time variables like waiting_list and buy_prices | Python Class Object |
| Signals | Quantitative triggers for market entry/exit | Array/List |
| ContextInfo | QMT-provided environment and market data object | API Object |
| Risk Metadata | Defines stop-loss ratios, max positions, and capital ceilings | JSON/Dictionary |
Quant Strategy Dev Advanced Features
- Synchronized Logic Engine: Guarantees that backtesting and live trading use 100% identical code paths.
- Deduplication Mechanism: Integrated waiting_list to prevent duplicate order placement during high-frequency signal triggers.
- Multi-Exit Logic: Comprehensive sell-side logic covering signal expiration, take-profit, stop-loss, and trend reversal.
- High-Precision Execution: Specialized passorder configuration (prType 14) for controlled slippage and professional counterparty pricing.
SKILL.md
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