Historical vs Monte Carlo inflation
Both modes use the same underlying historical dataset (roughly 1928–2025): annual CPI and asset-class returns. The difference is how years are chosen.
Historical run (single scenario)
When you set a start year, the calculator runs that period in calendar order. For example, start 1980 with a 30-year horizon uses 1980, 1981, 1982, and so on.
- CPI: each year uses that calendar year’s inflation from the dataset.
- Returns: portfolio returns use the same calendar year’s market data.
- Spending: income targets you enter in today’s dollars are inflated each year using that period’s CPI so real purchasing power stays on target.
Monte Carlo simulation
Monte Carlo runs many trials (1,000 by default). In each year of each trial, the engine picks one random historical year from the dataset.
- CPI and returns are paired: that year’s CPI and that year’s portfolio returns are always taken from the same
- Real return: the engine converts to a real (after-inflation) return, then subtracts your investment fee percentage.
real return ≈ (1 + nominal portfolio return) ÷ (1 + CPI for that drawn year) − 1 − investment fees
Years within a trial are independent random draws (with replacement). That is why Monte Carlo explores many possible sequences, not one actual past period.
In the calculator: open Monte Carlo Analysis → expand How inflation is modelled for a short summary, or use this page for the full explanation.
Monte Carlo “success %” vs your withdrawal strategy
The Monte Carlo target income is the annual amount (in today’s dollars) you want to test. The headline probability of success answers:
On how many random market paths could this fixed real income be paid (including minimum pension drawdown rules) without running out of super?
Floor and ceiling, dynamic SWR, and Vanguard guardrails: the detailed year-by-year results follow those strategy rules (spending can rise or fall with balance and guardrails). The success percentage does not re-run those rules inside every trial for the headline number—it tests your fixed target income against each path.
If strategy-driven spending differs from your target, compare the results table and median income paths to the success %, rather than expecting them to match exactly.
Fixed strategy: when you select a fixed withdrawal approach, the target income and the strategy align more closely, so the success % and the table are easier to compare side by side.
Run historical and Monte Carlo analysis in the Advanced Calculator.
Open Advanced CalculatorGeneral information only. Not financial product advice. Methodology reflects the SuperCalc Pro engine at the time of writing; confirm assumptions for your own modelling.