Why one average return number lies to you
Most retirement calculators ask for one number: your expected return. Type in 7%, and they draw a smooth line up and to the right. The problem? The market has never once delivered exactly 7% every single year. It gave you +28% in 2013, then -18% in 2022. That smooth line is a fantasy, and the fantasy can bankrupt you.
Here's what they don't tell you about that 7% average. Two retirees can both earn a 7% average over 30 years and end up in completely different worlds. The difference is sequence of returns risk (the order in which good and bad years arrive). If a 35% crash hits in your first two years of retirement while you're also withdrawing money, you sell shares at the bottom and never recover. The same crash at year 25 barely dents you.
A Monte Carlo simulation fixes this by refusing to use a single number. Instead, it runs your plan thousands of times, each run drawing a different random sequence of yearly returns from a realistic range. One run might hand you a brutal early bear market. Another gives you a roaring first decade. After 1,000 or 10,000 runs, you don't get one answer, you get a distribution: the percentage of simulated lifetimes where your money outlasts you.
That percentage is your success rate. If 850 out of 1,000 runs leave you with money at age 95, your plan has an 85% success rate. The other 150 runs are the ones where you ran dry, and they're not hypothetical, they're the same market history that already happened, just reshuffled. Most planners consider 85% to 90% a reasonably safe target. A 70% success rate means roughly one in three futures end with you out of money in your 80s. That is the number a single-return calculator hides from you completely.
Consider two retirees who both start with $1 million and withdraw $50,000 a year, a textbook 5% withdrawal rate. A flat calculator using a 7% average says both are fine forever. But run them through Monte Carlo and the picture splits. The retiree who happens to draw a strong first decade sails through with millions left over. The one who draws a 2000-style or 2008-style crash in years one through three watches the portfolio drop to $650,000 while still pulling $50,000 out, and the math never recovers. Same starting balance, same average return, same withdrawal, two completely different endings. The simulation is the only way to see that fork in the road before you're standing at it.
The famous 4% rule came directly from this kind of analysis. Researchers found a portfolio could sustain a 4% first-year withdrawal (adjusted for inflation after) across nearly every historical 30-year window. But "nearly every" is the whole point. This tool lets you stress-test your own numbers instead of trusting a rule built for someone else's portfolio.