A fast, scriptable crypto futures backtesting engine supporting multiple exchanges and technical indicators.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install crypto-backtest
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 crypto-backtest 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 Crypto Backtest Engine?
The Crypto Backtest Engine is a robust tool designed for quantitative traders and developers looking to validate trading strategies across various cryptocurrency exchanges. By leveraging the ccxt library, this skill allows users to fetch historical OHLCV data and simulate trades using built-in indicators like EMA, RSI, MACD, and Bollinger Bands. It is an essential addition to any developer workflow focused on Openclaw Skills, providing a structured way to evaluate market edges and risk management parameters before deploying capital.
Built with performance in mind, the engine supports futures trading simulations with configurable leverage and position sizing. Whether you are building an automated trading bot or conducting academic research, this skill provides the necessary framework to turn raw market data into actionable intelligence.
Crypto Backtest Engine Use Cases
- Validating crypto trading strategies against historical exchange data.
- Performing automated parameter sweeps to find optimal indicator settings.
- Calculating risk metrics like maximum drawdown and profit factor for futures trading.
- Building a quantitative research pipeline integrated with AI coding agents utilizing Openclaw Skills.
- Testing custom technical indicators through a standardized plugin interface.
How Crypto Backtest Engine Works
- Select a trading pair and an exchange supported by the ccxt library (e.g., Binance, Bybit, OKX).
- Define strategy parameters such as EMA periods, RSI thresholds, or Bollinger Band deviations.
- Configure account settings including initial capital, leverage, and trading fees.
- Fetch historical market data (OHLCV) automatically via the internal engine scripts.
- Run the simulation to execute trades based on the selected logic and calculate performance metrics.
- Review the generated JSON export to analyze trade-by-trade performance and equity curves.
Crypto Backtest Engine Setup
Install the necessary dependencies using pip:
pip install ccxt numpy
Run a basic EMA crossover backtest with specific parameters:
python scripts/backtest_engine.py --symbol ETH/USDT:USDT --strategy ema --fast 12 --slow 26
To perform a multi-strategy sweep across multiple indicators, use the sweep utility:
python scripts/sweep.py --symbol ETH/USDT:USDT --strategies ema,rsi,macd,bbands --capital 1000 --leverage 5 --output results.json
Crypto Backtest Engine Data Schema & Taxonomy
The skill organizes its data and outputs through a series of structured files and metadata:
| Component | Description |
|---|---|
| Market Data | Historical OHLCV data fetched from ccxt-supported exchanges. |
| Performance Metrics | Includes Total trades, win rate, profit factor, max drawdown, and final balance. |
| JSON Export | Machine-readable results containing trade logs and summary statistics for integration. |
| Strategy Definitions | Python scripts located in the scripts/ directory that define entry and exit logic. |
| Reference Docs | Markdown files documenting custom strategy implementation and edge cases. |
Crypto Backtest Engine Advanced Features
- Multi-exchange compatibility supporting any exchange integrated within the ccxt ecosystem.
- Automated parameter sweep runner for testing thousands of indicator combinations simultaneously.
- Comprehensive risk simulation including configurable leverage, stop-loss (SL), and take-profit (TP) levels.
- Extensible plugin interface for developing and testing proprietary custom strategies easily.
- High-density performance reporting specifically optimized for Openclaw Skills automation and pipeline integration.
SKILL.md
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