Quick Stats

The quick-stats skill provides immediate numerical summaries of backtest results without generating full reports. It calculates key performance metrics like total return, annualized return, and drawdown directly from VectorBT dataframes or result objects.

When to use it

• You need a rapid snapshot of portfolio performance before diving into detailed analysis.
• You are iterating through multiple trading strategies and want to compare their basic stats side-by-side.
• You require specific metrics (e.g., Sharpe ratio, max drawdown) for a dashboard or alert system without waiting for verbose output.
• You need to validate if a backtest result meets minimum viability thresholds quickly.

Key capabilities

• Calculates total return and annualized return automatically.
• Determines maximum drawdown and average drawdown from equity curves.
• Computes Sharpe ratio, Sortino ratio, and Calmar ratio based on input data.
• Accepts VectorBT BacktestResult objects or pandas Dataframes as input.
• Returns a concise dictionary of metrics rather than a full narrative report.

Example prompts

• "Calculate the quick stats for this backtest result: [insert result object]"
• "What are the total return and max drawdown for the strategy defined in this dataframe?"
• "Give me the Sharpe ratio and annualized return for the provided VectorBT output."

Tips & gotchas

Ensure your input data is a valid BacktestResult or pandas DataFrame containing an 'equity' column; otherwise, the skill cannot compute drawdowns. This skill focuses on numerical outputs only, so it will not provide textual explanations of why performance occurred.