Run a Monte Carlo simulation on your retirement plan and you get one headline number back. If it says 84%, the immediate question is whether 84% is good enough. For most plans it is. The standard planning target is a success rate between 80% and 90%, and a result inside that band means the plan is in healthy shape.
The better question is why that band is the target, and where inside it your own number should sit. The answer depends on facts the simulation cannot see: how much of your spending you could cut in a bad year, how much of your budget is covered by Social Security or a pension, and how many decades the plan has to run. This article covers the convention, the reasoning behind it, and the adjustments for your situation.
The success rate is the share of simulated futures in which your money lasts to the age you set. A plan that survives 850 of 1,000 randomized return sequences reports 85%. The other 150 runs are futures where the portfolio ran dry early, and they are concentrated among the sequences that open with a crash. Our guide to reading Monte Carlo results covers what the number measures and how to steer a plan with it; this article takes up the narrower question of what number to aim for.
Among practitioners, the working convention is a target in the 75–90% range, with 80–90% as the band most planning software and most advisors treat as healthy. The convention follows from two facts about the simulation. First, the failed runs are not spread evenly across ordinary futures; they are the extreme tail, the sequences that pair a deep early crash with years of stubborn inflation. Second, the simulation assumes you never react. Every failed run is a future in which you kept withdrawing the same inflation-adjusted amount while your portfolio fell apart for a decade. Real retirees do not behave that way. Michael Kitces, one of the most widely cited researchers on Monte Carlo use in financial planning, has argued the metric is better read as a "probability of adjustment": a failed run is not a future where you go broke, it is a future where you would have had to cut back for a while.
The target band: 80–90%. Below 80%, modest changes now buy real safety. Above 90%, each extra point mostly buys money you will not live to spend.
A 100% score requires your plan to survive every sequence the model can produce, including tails worse than anything in market history. The model manufactures those tails on purpose; that is what stress-testing means. Clearing them has a price, and the price is paid in every future, not just the bad ones.
The arithmetic makes the trade concrete. As a rough rule, pushing a typical 30-year plan from around 90% to around 99% means cutting the withdrawal rate by close to a percentage point, say from 4% to 3%. On a $1 million portfolio that is $10,000 less to live on every year of retirement. The cut applies in all 1,000 simulated futures, but it only matters in the hundred or so where the bad sequence shows up. In roughly nine futures out of ten you paid the premium and never needed it, and the unused premium appears at the end of the plan as a large balance you did not spend.
A 99% plan therefore usually means retiring later than necessary or spending less than the portfolio could support. Underspending has a cost too. It is just one that never shows up in the simulation.
Failure in the simulation means one specific thing: the portfolio could not fund the full budget, every year, to the end of the plan. How bad that outcome would be for you in practice is what sets your target.
If a quarter of your budget is travel, gifts, and other spending you could pause in a bad market, a stretch of weak returns forces trims, not ruin. Plans with that kind of slack can sit at the low end of the band, and a spender with a lot of slack can defend a target as low as 75%. If your budget is nearly all essentials, a bad sequence demands cuts you cannot make, so aim for the high end.
Social Security keeps paying whatever the market does, and so does a pension. If that floor covers your essential expenses, a depleted portfolio means losing extras rather than the roof. If the floor covers only a small share of essentials, portfolio failure is a much harder landing, and the target should move up accordingly. This is also why claiming decisions interact with the target: delaying Social Security raises the floor for life, which lets you accept a lower score on the portfolio side.
A 30-year horizon is the well-studied case. A 45- or 50-year horizon, the kind an early retiree needs, gives tail risks more time to appear and assumptions more time to drift. It also gives you more room to adapt, since a 45-year-old can return to work in a way a 75-year-old cannot. On balance the longer horizon argues for a higher target and for re-running the plan more often. Our piece on the 4% rule and early retirement works through why long horizons punish fixed withdrawal rules.
| Situation | Reasonable target |
|---|---|
| Guaranteed income covers essentials; spending has real slack | 75–85% |
| Typical mix of fixed and flexible spending | 80–90% |
| Tight budget, thin guaranteed income floor | 85–95% |
| Retiring in your 40s or early 50s | 85–95%, re-run yearly |
The headline number counts failures without weighing them. A run that goes broke at age 93 counts the same as a run that goes broke at 78, and the difference between those two futures is enormous. Two plans can both report 85% while one fails late and shallow and the other fails early and deep.
So look underneath the score. Check what age the failed runs give out at, and where the median path ends up. Most failures trace to the same mechanism: weak returns in the first several years of withdrawals, when each dollar sold is sold cheap. Our article on sequence-of-returns risk shows the mechanics with two retirees who earn identical average returns in opposite order and end up in opposite places.
At around 1,000 runs, a Monte Carlo result settles to within a point or two of itself. Re-run the same plan and 86% may come back as 85% or 87%. That wiggle is sampling error, not a change in your retirement. It follows that fine-tuning a plan to move the score from 86 to 88 is engineering inside the margin of error. Read scores in bands. A move from 72 to 84 is signal. A move from 84 to 86 is not.
Aim for 80–90%. Sit low in the band if your spending has slack and guaranteed income covers your essentials; sit high if your budget is rigid, your floor is thin, or your horizon is unusually long. Above roughly 95%, the more useful reading is that you can spend more or retire sooner. Below roughly 75%, adjust a lever: spending, retirement date, savings rate, or claiming age.
The target only means something once you have your own number. Run your plan through the calculator, see where it lands, and test which lever moves it the most. The Monte Carlo guide covers the mechanics behind the score if you want to see how the runs are built.
Run a Monte Carlo simulation on your numbers, see where you land against the 80–90% band, and test which lever buys the most points.
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