That Number on Your Financial Plan Screen? Here’s What It Actually Means.
You’ve Probably Seen a Number Like This…
Your financial plan says you have an 84% probability of success. Or 91%. Or 76%.
That number comes from a tool called Monte Carlo simulation. Your advisor runs thousands of hypothetical futures through a computer — some with strong markets, some with terrible ones — and counts how many of those futures end with money still in the portfolio. The percentage that “make it” is your probability of success.
It’s a compelling idea. And it is genuinely useful. But there are important things that number doesn’t capture — and we think you deserve to understand what those are.
“84% probability of success” is a starting point for a conversation, not the final answer.
How the Simulation Works — In Plain English
Imagine you put all of history’s annual market returns into a hat. A good year, a terrible year, a mediocre year, a great year — each on its own slip of paper. The Monte Carlo engine draws from that hat one year at a time, for 30 years, thousands of times over.
It assumes each draw is completely random and independent — the way a coin flip doesn’t “remember” what happened on the last flip. Run it enough times, and you get a wide range of possible futures.
This is clever. But real markets don’t work quite like a hat full of slips.
Where the Model Falls Short
Here are the gaps that matter most for your actual retirement:
Timing matters enormously — and the model undersells this.
Here’s something counterintuitive: two people can retire with the exact same nest egg, earn the exact same average return over 30 years, and end up in completely different financial situations — depending on which years the bad markets happened.
If you retire right before a major downturn and are withdrawing money while the market is dropping, those early losses hit harder than you might expect. You’re selling shares at low prices to cover expenses, which means you have fewer shares to benefit from the eventual recovery. A rough sequence early in retirement is genuinely more dangerous than the same rough years happening in your 80s.
Monte Carlo captures this in the math, but the “probability of success” number can make it feel more abstract than it is. We always stress-test your plan against the worst historical sequences we know of: 1929, 1966, 2000. Because if your plan survives those, we’re confident.
Real crises are wilder than the model expects.
The simulation assumes bad years are roughly as bad as the average bad year in history. But genuine financial crises — 2008, March 2020, the dot-com collapse — tend to be more severe and more correlated across asset classes than the model predicts.
In plain terms: when things get really bad, everything tends to go down at once. The “diversification” that protects you in normal times provides less cushion in a real crisis. A simulation that doesn’t fully account for this will give you a probability of success that’s a touch more optimistic than reality.
You are not a static withdrawal machine.
The model assumes you will spend the same amount every single year, no matter what the market does. But that’s not how real people behave — and it’s probably not how you’d behave either.
If the market drops 30% in year two of your retirement, most people naturally cut back on discretionary spending. They delay the kitchen renovation, take a smaller vacation, give a little less to the kids that year. That flexibility is actually a huge asset — and it’s one the simulation ignores entirely.
A plan built around that kind of intentional flexibility — what planners call a “guardrails” approach — performs better than a rigid withdrawal plan, and it’s closer to how you’ll actually live.
Your real life has options the model can’t count.
You might do some consulting. You might sell a property. You might delay Social Security. You might decide the lake house isn’t worth the maintenance at 78. These real options have real financial value, and none of them show up in the probability of success figure.
A “failure” in the simulation might mean adjusting your travel budget at 62. That’s not the same as running out of money.
So, Why Do We Still Use It?
Because, for all its limitations, Monte Carlo is still the best tool we have for turning uncertainty into something you can see and respond to. It forces a real conversation about risk, spending, and flexibility. It helps us identify which levers matter most for your particular situation.
We just don’t stop there.
What we do instead of just handing you a number:
We run historical stress tests alongside the simulation — modeling you how your plan would have fared if you had retired in 1973, 2001 or 2008.
We model what happens when you flex your spending, not just when you hold it rigid.
We factor in your other resources: Social Security timing, real estate, part-time work, and any inheritance you might receive or give.
We build in tax strategy at every step — because how much you keep after taxes matters as much as what the market returns.
We revisit the plan regularly. A plan that gets updated when life changes is far more valuable than a perfect plan that sits in a drawer.
The Bottom Line
That probability-of-success number is a useful piece of information. It’s not a verdict. Real financial security comes from a plan that’s designed to flex, adapt, and stay honest about what we know and don’t know about the future.
That’s what we try to build with every client. And it’s why we’d rather have a real conversation about your plan than hand you a percentage and call it done.
Questions about your plan or how we’re modeling your retirement? We’d love to talk. Reach us at laylinefin.com.
Layline Financial is a fee-only registered investment advisor. This article is for educational purposes only and does not constitute personalized investment or financial planning advice.
