Monte Carlo Simulations: What They Tell You (And What They Don't)
What a Monte Carlo Simulation Really Tells You About Your Retirement Plan
If you've reviewed a retirement projection with us, you've probably seen a number like "87% probability of success." That number comes from a Monte Carlo simulation — one of the most useful tools in retirement planning, and also one that can be misunderstood.
Here's what it actually does, what that percentage really means, and — just as important — what it can't tell you.
What Is a Monte Carlo Simulation?
A traditional retirement projection often assumes a single, steady rate of return every year — say, 6% — for the rest of your life. The problem is that markets don't work that way. Returns are lumpy. Some years are up 20%, some are down 15%, and the order those returns happen in matters enormously, especially once you start withdrawing money.
A Monte Carlo simulation accounts for this by running your plan not once, but usually a thousand times, each time using a different, randomly generated sequence of investment returns and inflation rates. Each run is a different possible version of the future. Some include periods that look like the 2010s. Some include years that look like 2008. Some look like nothing we've seen before.
At the end, we look at how many of those thousands of trials ended with your money lasting as long as you wanted it to. If your plan succeeds in 870 out of 1,000 trials, that's your "87% probability of success."
What That Percentage Actually Tells You
It tells you how resilient your plan is to sequence of return risk and inflation risk. This is the simulation's real strength. It's not testing whether markets will average 7% or 8% over the next 30 years — it's testing what happens if you retire right before a downturn, or if inflation runs hot for a stretch while you're drawing down assets. A high success rate means your plan can absorb a run of bad luck early in retirement for example, which is historically the biggest threat to a retirement portfolio.
It gives you a way to compare decisions (scenario analysis). Should you retire at 63 or 65? Should you increase your savings rate by 2%? Should you identify flexible spending strategies to account for possible down years? Monte Carlo results let us test these scenarios against each other and see which ones move the needle most, in a way a single fixed-return projection simply can't.
It's a planning tool, not a prophecy. The number is meant to inform a conversation, not end one. A result of 72% isn't a grade — it's information about where the pressure points in your plan are and what levers are available to strengthen it.
What the Simulation Doesn't Tell You
It doesn't predict what will actually happen. An 87% success rate does not mean there's an 87% chance your specific future unfolds a certain way. It means that out of a thousand hypothetical, randomly generated markets, 87% of them didn't break your plan. The real future will be exactly one path, not a distribution of them — and it may not resemble any of the market histories the simulation drew from.
It doesn't know the unknown. The simulation models numbers: returns, inflation, withdrawal amounts. It doesn't know things such as when and to what extent a major health event might change your spending. Scenario analysis and stress testing the plan can help with this, but what actually happens in the future is still unknown.
It doesn't account for the actions you'd actually take. Most simulations assume you keep spending on the same track no matter what the market does. In reality, if markets fall sharply in year one of retirement, you'd likely adjust — spend a bit less for a while, delay a big purchase, or postpone a Social Security claim. That flexibility, which we build into your real plan, tends to make outcomes better than the raw simulation number suggests.
A "failure" in the simulation isn't a cliff. A failed trial usually means the money technically ran short of your goal – maybe it lasted 27 years of a 30-year retirement, not that you woke up broke on day one. In practice, a low success rate is an early warning system, not a countdown clock. It's telling us to look at the plan now, while there's time to make small adjustments, rather than waiting for a crisis.
It's only as good as its assumptions. The ranges of possible returns, inflation, and volatility built into the model are estimates based on history and current market conditions. Change those assumptions and the percentage changes too. This is one of the reasons we don't treat any single number as gospel — we look at how sensitive your plan is across a range of reasonable assumptions.
The Real Value: A Conversation, Not a Verdict
Think of a Monte Carlo simulation less like a weather forecast and more like a stress test. It's less useful for telling you exactly what will happen and more useful for telling you how much shock your plan can absorb before it needs attention — and where that attention should go.
That's why we don't just hand you a percentage and move on. We use it to identify:
Where your plan is strong
Where it's sensitive
What specific choices — spending flexibility, retirement timing, savings rate, portfolio structure — would do the most to improve your odds
If it's been a while since we've run or reviewed your projection, or if your circumstances have changed, it's a good time to revisit it together. The number itself is just the starting point for the conversation that actually matters.
Stephanie H. Murray, EA, CFP®
Planning and Operations Manager
Find out more about Stephanie on her profile page here! Be sure to listen to her episode on Finance in a Flash to hear what got her interested in Financial Planning!