PATH TO FI™ · BLOG

Will Your Money Outlive You?

October 6, 2026 · 6 min read · By Prakash Damodaran

"Will my money outlive me?" is the question every retirement plan is really trying to answer, and it is unanswerable in the way we want. Nobody can tell you what markets will do over the next thirty years. But there is an honest substitute for a prophecy: a probability. And the tool that produces it is called a Monte Carlo simulation.

The name sounds intimidating. The idea is not. A Monte Carlo simulation runs your retirement plan through thousands of different simulated futures and counts how many of them end with money left. That count, expressed as a percentage, is your probability of success. Here is what that number means, what it does not mean, and how the withdrawal rate you choose moves it.

What is a Monte Carlo simulation?

It is named after the casino in Monaco, because it runs on randomness. Here is the plain version: take your starting portfolio, your planned annual spending, and your time horizon. Then simulate one possible future by drawing a sequence of yearly investment returns, good years and bad years in a random order, drawn from historical market data. Run that future to the end and check: is there money left?

Now do it again. And again. Two thousand times, each with a different random sequence of returns. Some futures get the bad years early, some get them late, some barely get any. Count how many of the 2,000 end with money in the account. If 1,700 survive, your success probability is 85%. That is the whole technique: many futures, one count, one honest number.

Why is the answer a probability, not a prophecy?

Because you will live exactly one future, and the simulation cannot tell you which one. An 85% success rate means 850 out of 1,000 simulated futures worked and 150 ran out of money. It does not mean you are 85% fine. It means that if the future deals you an average hand of luck, you are fine, and if it deals you a bad one, you are not.

This is more useful than it sounds. A probability tells you how much luck your plan needs. A plan with a 95% success rate needs only a little luck. A plan with a 60% success rate needs a lot. Nobody can promise you which future you get, but you can absolutely choose a plan that needs less luck. That is what the number is for.

How does your withdrawal rate move the odds?

The withdrawal rate is the biggest lever you control. Spend less of your portfolio each year and more simulated futures survive; spend more and fewer do. The relationship is direct and unforgiving, because every extra point of withdrawal has to survive every bad sequence the simulation throws at it.

Think in the three standard choices. At 3%, a 33x portfolio, the vast majority of simulated futures survive, even the ugly ones with early crashes. At 4%, a 25x portfolio, most futures still survive, which is why 4% is the standard starting point for a thirty-year horizon. At 5%, a 20x portfolio, meaningfully fewer futures make it; the margin for bad luck is thin. The lever is spending, not returns: you cannot control what markets do, but you control the rate you draw.

This is also why the FI formula and the simulation agree with each other. FI number = (recurring annual spending / chosen withdrawal rate) + planned one-time expenses, in today's dollars. A lower rate means a bigger number and better odds. A higher rate means a smaller number and worse odds. There is no free choice here, only a trade you make with your eyes open.

Why does the order of returns matter so much?

Because withdrawals turn a bad early sequence into permanent damage. Imagine two retirees with the same portfolio and the same average returns over thirty years. One gets the crash in year two, the other in year twenty-five. The first sells investments at rock-bottom prices to fund living expenses, and those shares never recover. The second rides out the crash with a portfolio that has had decades to grow. Same average return, wildly different outcomes.

This is sequence-of-returns risk, and it is the main reason Monte Carlo simulations exist. A single average return cannot capture it; only thousands of different orderings can. The futures that fail in a simulation are overwhelmingly the ones where the bad years arrive early. That is also why the first five to ten years of withdrawals deserve the most caution, and the most margin.

What can't the simulation tell you?

First, it assumes the future will roughly resemble the past, because its random draws come from historical returns. That is a reasonable assumption and an unproven one. Markets could deliver decades worse than anything in the data, or better. The simulation measures the risks we have seen, not the ones we have not.

Second, and this cuts in your favor, the simulation assumes you are a robot. It assumes you withdraw the inflation-adjusted amount every single year no matter what, even as the portfolio craters. Real people do not do that. Real people skip the big vacation in a crash year, delay the renovation, pick up part-time work. That flexibility raises your real odds above what the model shows. The simulation is your plan's pessimistic twin: if the robot survives, you almost certainly do.

How often should you re-run it?

Once a year is plenty, plus after any big change: a market crash, a large expense, a decision to retire earlier or later. The simulation is a compass, not a dashboard; checking it daily adds anxiety without information. What you are watching for over time is drift: has your spending crept up, has your portfolio fallen, has your horizon shortened? Any of those changes the odds, and the honest move is to see it.

Treat each re-run as a planning input, not a grade. A lower probability than last year is not a failure; it is early information, while you still have options. Cut spending a little, save a little more, delay a year. Small adjustments early beat big adjustments late. That is the entire value of the tool.

How should you use the number?

Run the what-ifs, then make a human decision. Test 3%, 4%, and 5% side by side and watch the odds move. If 4% gives you a probability you can live with and 5% gives you one you cannot, you have learned something real about your plan for the price of an afternoon.

Then choose the rate whose failure odds you could honestly accept, and build in a margin on top. Probability is the honest answer to a question nobody can answer for sure: not a promise, not a prophecy, just the clearest picture available of how much luck your plan needs. Choose a plan that does not need much.

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