skfolio-powered allocators across US equities and global index universes. Click any model to open its dedicated page.
Portfolio optimization comparing Max Sharpe, Min Variance, Equal Weight, Inverse Volatility, Max Diversification, and Risk Parity — with equity curves, drawdowns, rolling Sharpe, return distributions, and weights.
Generated Tuesday, Jul 7, 2026
Built with the skfolio library. US portfolio uses a subset of S&P 500 stocks; global portfolio uses major equity indices. Models are fitted on historical daily returns — transaction costs not modeled.
80 assets · Select a model to view metrics and plots
What this shows: Model-level risk/return scatter: volatility on x-axis, total return on y-axis, bubble size by Sharpe.
How to read it: Higher and leftward points with larger bubbles are generally better risk-adjusted candidates.
What this shows: Overlayed wealth-index curves for all optimization models.
How to read it: Compare long-run slope and drawdown/recovery behavior to spot robust models rather than single-period winners.
What this shows: Selected model wealth-index path over time (Equal Weight).
How to read it: Steadier ascent with smaller interruptions is typically preferable to highly jagged paths with similar endpoint return.
20 assets · Select a model to view metrics and plots
What this shows: Model-level risk/return scatter: volatility on x-axis, total return on y-axis, bubble size by Sharpe.
How to read it: Higher and leftward points with larger bubbles are generally better risk-adjusted candidates.
What this shows: Overlayed wealth-index curves for all optimization models.
How to read it: Compare long-run slope and drawdown/recovery behavior to spot robust models rather than single-period winners.
What this shows: Selected model wealth-index path over time (Equal Weight).
How to read it: Steadier ascent with smaller interruptions is typically preferable to highly jagged paths with similar endpoint return.