Traditional retirement calculators use a single assumed rate of return — typically 7% — to project whether a client will have enough money. The problem? Markets don't return a steady 7% every year. Some years they're up 20%, others they're down 30%.
Monte Carlo simulation solves this by running thousands of scenarios (we use 10,000) with randomized annual returns based on historical data. Each scenario represents one possible path the market could take over your client's retirement.
The result is a probability of success — for example, "87% of scenarios show your money lasting to age 95." This is far more useful than a single projection because it captures the impact of sequence-of-returns risk, inflation variability, and market volatility.
Key metrics from a Monte Carlo analysis include percentile bands (p10 through p90), which show the range of outcomes. The median (p50) represents the "most likely" scenario, while p10 shows what happens in poor market conditions.
For advisors, this changes the conversation from "you'll have $2 million at retirement" to "there's an 87% chance your money lasts." It sets realistic expectations and helps clients understand the value of saving more, adjusting spending, or delaying retirement.