Backtest
Analyzes past trading data to evaluate strategy performance & identify potential improvements for future investments.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add backtest npx -- -y @trustedskills/backtest
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"backtest": {
"command": "npx",
"args": [
"-y",
"@trustedskills/backtest"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The backtest skill allows users to simulate the performance of trading strategies using historical financial data. It leverages vectorized backtesting libraries for efficient and accurate analysis, enabling users to evaluate how a strategy would have performed in past market conditions.
When to use it
- To test the effectiveness of a new trading algorithm before deploying it live.
- When analyzing historical price patterns to identify profitable opportunities.
- For comparing multiple strategies side by side using real-world data.
- During portfolio optimization to refine entry and exit rules based on past performance.
Key capabilities
- Simulates trading strategy performance with historical market data
- Supports vectorized backtesting for speed and efficiency
- Provides detailed performance metrics like returns, drawdowns, and risk ratios
Example prompts
- "Backtest a moving average crossover strategy using S&P 500 data from 2010 to 2023."
- "Simulate the performance of a long-only portfolio with monthly rebalancing over the last decade."
- "Compare the returns of two different risk management models on NASDAQ historical prices."
Tips & gotchas
- Ensure you have access to high-quality, clean historical market data for accurate results.
- Be mindful of overfitting—test strategies on out-of-sample data to avoid misleading performance metrics.
Tags
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