Monte Carlo Simulation
Testing a plan against thousands of randomized return sequences instead of one average.
A single projection line assumes the same return every year, which no market has ever delivered. Monte Carlo instead draws thousands of return sequences from a distribution and runs the full plan against each, then reports how many finished solvent.
The output is a success rate rather than a balance. A plan working in 8,700 of 10,000 sequences reports 87%, and the number is meaningful mainly in comparison: whether a change moves it up or down, and by how much.
It carries real limitations worth naming. The result depends entirely on the assumed distribution of returns, and drawing years independently understates the tendency of markets to trend and mean-revert. A success rate is a statement about the model, not a forecast, which is why the direction of a change is more trustworthy than the level.
Worked through
Your Retirement Plan Success Rate
This plan: 87% of 10,000 sequences
Where this lives in Promi
Investing page. The retirement tab runs Monte Carlo on your own balances and spending.
Related in FIRE & Financial Independence
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