Monte Carlo & simulation guides

What this topic covers

A single projection assumes one average return every year. Markets do not behave that way: a bad decade early in retirement can exhaust a portfolio that would have survived the same average return in a different order. Monte Carlo simulation addresses this by generating thousands of return paths from an assumed distribution and counting how many fund the spending plan.

The output — often called a success probability — is not a promise. It is only as good as its inputs: expected return, volatility, inflation, fees, taxes and the withdrawal rule. A 90% figure with optimistic assumptions can be less informative than a 75% figure with conservative ones. Read it as a range of outcomes and a prompt to stress-test, not a pass mark.

Learn why the order of returns matters in the sequence-of-returns guide, then run your own numbers in the retirement planning calculator or the dedicated Monte Carlo tool.

Guides in this topic

• How Monte Carlo Simulation Works (and Its Limits)

  8 min read • Updated 2026-10-18

  Monte Carlo tests thousands of possible return paths for your retirement plan, so you can judge probability — not prediction. Here's how to read the results.