Turn portfolio history into performance reports.
Evaluates portfolio returns and risk from equity curves and trade logs, producing performance metrics and HTML reports.
When to use it
Use after backtesting, to compare strategies, prepare investor reports, evaluate live performance, or assess returns for allocation decisions.
Give it portfolio equity curves and optional trade logs; it returns performance analysis and can generate an HTML report.
What you provide
The bundled analysis script runs with Python 3.
The documented dependency installation command uses uv.
Requires pandas for the portfolio time series and analysis.
This skill
uv pip install pandas numpy quantstats
Installs portfolio analysis libraries