Should You Aim for 100% Success in Monte Carlo Retirement Simulations?
Monte Carlo simulations are a staple in retirement planning. They run thousands of potential future market scenarios to estimate how likely your portfolio is to last throughout retirement.
Monte Carlo projections can generate a number of outputs but one of the most commonly discussed is the Probability of Success.
It goes like this: “Based on our assumptions, you have a 90% Probability of Success”.
One question often comes up next: What about the other 10%?
This portion of the projection has been dubbed the “Probability of Failure” and can be a confusing or scary thing to see.
But what exactly does “failure” mean? And is it really bad if your plan isn’t showing a perfect 100% success rate?
What "Failure" Means in Monte Carlo
In Monte Carlo simulations, a “failure” doesn’t mean you’re broke and destitute.
It simply means that in that particular simulated scenario, your portfolio would have run out of money before the end of your planning horizon—say, before age 95 or 100.
Here is what that looks like:
Those lines that hit the bottom line before the projection runs out represent the probability of failure.
However, here are some good reasons why this is not necessarily a major concern:
- Projections often assume you continue to spend the same amount throughout retirement without adjusting for actual performance. Some projection software can include spending strategies that do adjust so it’s important to know what you’re dealing with.
- Results often don’t account for non-investment assets like equity in a home, rental properties, farm, or business.
- Running out of “money” doesn’t mean not covering a good lifestyle. Other sources of income such as Social Security, pensions or annuities could continue to provide more than enough income.
- Base assumptions could also result in scenarios so extreme that it may be a risk you’re willing to accept.
- Results don’t account for the timing of the failure. For example, a plan projecting to age 95 that runs out at age 94 and 364 days is still counted as a failure.
Is Any Probability of Failure “Bad”?
Not necessarily. Here’s why:
- Real life is adaptive. If things start looking rough—markets drop, inflation spikes—you can cut back spending, delay big purchases, or tweak your strategy. Those mid-course corrections aren’t in the simulation unless your planner builds them in.
- Conservative assumptions already reduce risk. Many simulations already assume modest returns, higher spending, or long lifespans—making “failure” less likely in real life than the raw percentage suggests.
- Targeting 0% failure can be overkill. Striving for absolute certainty often means spending much less than you could, leaving a large unused balance at the end of life. That’s money that could have funded experiences, gifts, or charitable giving.
Should You Aim for 100% Success?
n theory, 100% success sounds great. In practice, it often means you’re leaving a lot of lifestyle potential on the table.
Consider:
- Trade-offs – To push from 90% to 100%, you might have to cut spending by thousands per year, delay retirement, or take less market risk.
- Opportunity cost – That extra “safety margin” could represent vacations never taken, home improvements skipped, or gifts not given.
- Diminishing returns – The closer you get to 100%, the more lifestyle you give up for small increases in security.
The right target is hotly debated in retirement planning but many financial planners find that a success rate between 80–95% is reasonable for most retirees, assuming flexibility in spending. The sweet spot depends on your comfort with risk, your other income sources (Social Security, pensions, annuities), and how willing you are to adjust over time.
Bill Bengen, the creator of the 4% rule, used a 100% success rate based on historic returns but monte carlo simulations often spit out scenarios far worse that history.
Wade Pfau, a prominent retirement researcher, uses 90% to 95%.
David Blanchett, a prominent retirement research, uses 85% to 90%.
Michael Kitces, a prominent financial planning guru, uses 80% to 90%.
Jonathon Guyton and William Klinger, developers of the guardrails uses 80% to 85%.
Vanguard Research uses 85% to 90%.
JP Morgan uses 80% to 90%.
Schwab uses 85% to 90%.
Summary
A Monte Carlo failure rate is not a crystal ball predicting doom—it’s a statistical guidepost. The goal isn’t to hit 100% at all costs, but to find the right balance between confidence and enjoying the life you’ve worked for.
Planning is not an event or a single deliverable. It’s an ongoing conversation of your goals, resources, and risks. It’s setting a strategy, and adapting that strategy over time based on how your retirement unfolds.