How’s your retirement plan going? Chances are you have no idea—about one-fourth of Americans saving for retirement actually have no idea how much money they have salted away, and more than half of the people in the workforce who aren’t contributing to a 401(k) think that they are.
Retirement is confusing, and often stirs up feelings of anxiety and dread. Will you have enough to live on? Will you be able to handle medical expenses in a world where booking a vacation to have major surgery is sometimes the best financial decision? And, most dreadful of all, will you simply run out of money and spend your final days in poverty?
Fun stuff. Many people rely on financial advisors of one sort or another to reassure and guide them, and there are a lot of sophisticated tools used by those professionals to give us some idea of how we’re doing and what our eventual retirement might be like. But there are a lot of variables to consider, most of which are outside our control. As a result, if you’ve spoken to a professional about retirement planning, you’ve probably encountered what’s called a Monte Carlo simulation—or you will, soon. These tools are helpful, but they’re also deceptive, and you shouldn’t rely on their projections.
What’s a “Monte Carlo simulation”?
A Monte Carlo simulation is a sophisticated piece of software that takes a bunch of assumptions and variables, plugs them into a model, and runs hundreds or thousands (or even hundreds of thousands) of simulations to see how changing variables affect the outcome. Then it averages the outcomes to give you an idea of how likely various outcomes are.
In retirement planning, variables like inflation or market returns are given random values for each simulation. Run the simulation enough, and you get a general idea of how likely it is that your strategy will make your money last to a certain age. The results are typically displayed as a graph with a bell curve, where the most likely scenarios are in the middle and the outliers—the unlikely stuff—are at either end. You’ll also often be given a probability score that sums everything up; an 80% Monte Carlo score means your current plan has an 80% chance that your money will last.
Monte Carlo simulations are useful. They can test assumptions and reveal potential flaws in your plans or confirm that your strategy is sound. But the Monte Carlo score is often oversimplified, and you should never rely solely on a Monte Carlo simulation to confirm a retirement saving strategy, for four big reasons.
Monte Carlo simulations can’t predict the unexpected
Monte Carlo simulations only know the data plugged into them—and can’t possibly anticipate unexpected events in their calculations. For example, financial theorist William J. Bernstein once pointed out that if you retired in January 1966, the first 17 years of your retirement occurred when the market returns of the S&P 500 were almost perfectly matched by the rate of inflation (a period known as The Great Inflation), essentially making returns on your investments zero.
Monte Carlo simulations can’t possibly account for stuff like that—they rely on assessing probability, not sifting in once-in-a-century financial weirdness or unforeseen market crashes. Even if it gives you a score of 100%, the chances of success are always lower if you factor in the chance of the unexpected.
There are different models
Something else to consider when you get a Monte Carlo score from your financial advisor is the software itself. You can find free Monte Carlo simulators online, after all, and chances are you have no idea if your financial advisor is working with a super-sophisticated, AI-assisted monster of a simulation or a homebrew Excel spreadsheet they first created in 1999. You also can’t know the methodology being used under the hood. If you trust your advisor, it makes sense to trust their simulation, of course—but keep in mind that if the software itself stinks, so will its results.
Human error is a factor
Monte Carlo simulations have to make a lot of assumptions to run their models, and one of the most unreliable is that you—yes, you—will hold up your end of the bargain. You might tell your advisor that you plan to save a certain amount in your retirement accounts, cut down your spending when you retire, and be perfectly happy living a small, quiet life in a paid-off house—then go kind of nuts when you finally do retire and spend lavishly as you experience a kind of YOLO fever. In other words, these simulations often assume you will robotically do what you should do for decades and decades, despite the entirety of human history demonstrating how sketchy we all are.
The opposite is true, too. If your Monte Carlo score is low, the simulation doesn’t know that you’re actually quite adaptable and will change all your spending and saving habits on a dime the moment you sense trouble brewing in your accounts. The simulation thinks you’ll run out of money in 20 years, but you’ll find a way to make it last 40.
Does that mean the simulation is useless? No, it just means you can’t assume it tells you everything.
Monte Carlo scores can be deceptive
Finally, Monte Carlo scores can be deceptive if taken at face value. If you run 5,000 simulations and your money lasts through 4,000 of them, you get a score of 80%. That’s pretty good, right? But that also means your current plan failed 20% of the time—if you were told you had a 20% chance of dying if you did something, you probably wouldn’t be too complacent about it.
Plus, Monte Carlo scores can be changed just by tweaking the variables. Change the assumption about inflation rates, or assume that you’ll put an extra 5% of your income into your IRA, and that 80% might suddenly become 90%—but it doesn’t really mean much. All it can do is let you test out different scenarios and get a rough idea of how on—or off—the mark you are.
And that’s not nothing—Monte Carlo simulations have their uses. If nothing else they give you some idea of how your current retirement plan will work if things remain more or less as expected and you do exactly what you think you will (including, you know, living long enough for any of this to matter). But don’t make the mistake of hearing a high Monte Carlo score and assuming that you’re all set for the future.
