How ML Stats Calculates Portfolio Projections

The Portfolio Income Modeler estimates sustainability month by month using configured portfolio weights, annual price growth assumptions, annual dividend yields, and inflation-adjusted income targets.

What the model returns

• Summary metrics including final portfolio value, principal change, and shortfall totals.
• Yearly rollup totals for income targets, dividends, share sales, and ending value.
• Initial and final holdings snapshots under the configured strategy assumptions.
• Monthly time-series used for charts (portfolio value and target-vs-withdrawal).

Monthly simulation sequence

1. Convert annual growth assumptions to monthly compounding rates and apply to each holding.
2. Convert annual dividend yield to monthly income and add to cash balance.
3. Withdraw income target from cash first, then sell holdings if needed based on sale strategy.
4. Record any unmet amount as monthly shortfall.
5. If DRIP is enabled, reinvest remaining cash by current holding weights.
6. If rebalance cadence triggers, rebalance to target weights using total holdings plus cash.

Max monthly income mode

When enabled, the model runs repeated simulations to search for the highest monthly income that keeps ending value near a target within a configured tolerance band.

Important assumptions

• Annual growth and yield inputs are deterministic assumptions, not forecasts.
• Costs, taxes, slippage, and fees are not modeled.
• Override strings must use SYMBOL=PCT pairs separated by commas.
• The current version supports the predefined ETF universe used by the built-in portfolios.

Important note

Results are informational and educational. They are not guarantees of future investment performance.