backtesting-trading-strategies
Backtest crypto and traditional trading strategies against historical market data.
Works with
What it does
Includes 8 pre-built strategies (SMA, EMA, RSI, MACD, Bollinger Bands, Breakout, Mean Reversion, Momentum) with customizable parameters
Calculates comprehensive performance metrics: Sharpe, Sortino, Calmar ratios, max drawdown, VaR, volatility, win rate, and profit factor
Supports parameter grid search optimization to find best-performing configurations across strategy parameters
Generates trade-by-
Installation Guide
How to use backtesting-trading-strategies on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
backtesting-trading-strategies
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches backtesting-trading-strategies from gracefullight/stock-checker and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate backtesting-trading-strategies. Access via /backtesting-trading-strategies in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
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