portfolio-analytics

To calculate risk-adjusted performance metrics from an equity curve, this Skill computes total return, CAGR, Sharpe ratio, Sortino ratio, and maximum drawdown. It transforms raw equity data into actionable insights for evaluating investment portfolio performance.

To generate a quantstats HTML report for a backtested trading strategy, this Skill integrates directly with the quantstats library. It processes your equity curve to produce detailed HTML reports containing performance metrics, risk assessments, and monthly return tables.

For portfolio analysis using pandas and numpy, you can compute volatility, Value at Risk, and time spent underwater. This Skill leverages these dependencies to quantify risk metrics and generate rolling statistics from your equity curve data.

Yes, this portfolio analysis approach supports monthly return tables and drawdown analysis. It processes equity curves to calculate maximum drawdown, time spent underwater, and monthly returns, providing a comprehensive view of investment performance.

Yes, you can use this Skill to evaluate the viability of a trading strategy after backtesting. It takes your equity curve data and generates a full performance report, including risk-adjusted metrics and a monthly return heatmap, to assess investment viability.