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Why single-number projections lie — and how 1,000+ scenarios gives you a realistic picture of what retirement actually looks like.
Most retirement calculators work like this: assume a 7% average annual return, multiply by years, show you a number. It's clean. It's simple. And it's dangerously wrong.
Markets don't return 7% every year. They return +26% one year, -38% the next, +23% the year after. The average might be 7%, but the sequence of those returns — especially in the first few years of retirement — determines whether your money lasts.
Imagine two people retire with $1M on the same day. Person A experiences a 30% crash in year 1, then strong returns afterward. Person B experiences the same years in reverse order — strong first, crash at the end. Person A runs out of money. Person B is fine. Same average return. Completely different outcomes. Average-return calculators show them both surviving.
Instead of one projection, Monte Carlo runs 1,000 different market scenarios through your retirement plan. Each scenario uses a different sequence of annual returns drawn from realistic market distributions. At the end, it counts: how many scenarios ended with money remaining?
1,000+
Scenarios per run
30
Years simulated
4
Simulation models
The result is your success rate— the percentage of scenarios where you don't run out of money. A 90% success rate means 9 out of 10 market environments kept you financially secure. It also means 1 in 10 did not — which is why having backup levers (spending flexibility, part-time income) matters.
Your plan survives almost every scenario. You may be able to afford more spending in retirement, or you've saved well ahead of schedule.
Widely considered the target zone for a well-constructed retirement plan. Robust enough to handle most market environments.
Workable if you're willing to reduce spending by 5–10% in bad market years. Dynamic spending strategies can bridge this gap effectively.
A meaningful portion of scenarios end in portfolio depletion. Consider increasing savings, adjusting your retirement age, or reducing your income target.
Each model answers a different question about your plan's resilience.
Draws return sequences from actual historical market data (1926–present). Tests your plan against the Great Depression, the 1970s stagflation, the dot-com crash, and 2008. If your plan survives history, it has a strong foundation.
Generates synthetic return sequences using statistical properties of market returns — mean, standard deviation, fat tails. More scenarios than history alone, captures market behavior without being limited to what actually happened.
Randomly resamples blocks of historical returns (not just individual years) to preserve autocorrelation — the tendency for bear markets to cluster. Creates realistic multi-year downturns without assuming history repeats exactly.
Applies a 20% haircut to expected returns and increases inflation assumptions by 0.5%. Answers the question: "If the next 30 years are structurally worse than the historical average, what happens to my plan?"
Is 100% success really impossible?
Not impossible, but it requires enormous over-saving — far more than most people need. More importantly, chasing 100% means you're optimizing for the worst 0.01% of market scenarios. A better strategy is targeting 90%+ and building in spending flexibility for the remaining 10%.
Does Monte Carlo account for Social Security?
Yes. When you add Social Security income in your settings, it's modeled as a guaranteed income floor that reduces the portfolio withdrawal needed each year — which meaningfully improves your success rate.
Should I use all four models?
Looking at multiple models gives you a range — your plan's best case, expected case, and stress-tested case. If your plan survives the Conservative Stress Test at 80%+, you have a genuinely robust retirement strategy.
Free retirement calculator with all four simulation models. No credit card required.