Online Retirement Calculators Can Be Risky

by Randall Luebke RMA, RFC on October 4, 2011

By Taylor Smith
All the do-it-yourself financial tools on the Web may tempt clients and prospects to question the value of hiring an advisor. Counter that trend by explaining what you can offer that Monte Carlo-based predictions cannot.

Online investment calculators can be a little addictive.

Just plug in a couple of numbers and voilà! The screen tells you if your
retirement savings will actually last through retirement. Skip to the next
calculator and you can find out in less than a minute just how long it will take
to pay off your credit card, and how much interest it will cost you.

But while online calculators are a nice little diversion for Web-savvy
investors, can they really be trusted? Monty Hothersall doesn’t think so.

Hothersall is the cofounder of Financial Modeling Solutions, an Atlanta-based
company that makes the tracking software Financial Fate. When Hothersall and
cofounder Aydren Simmons were building Financial Fate in 2004, they opted
against using the same kind of mathematical engine—a Monte Carlo simulation—that
drives many online retirement calculators. “What we found out is that there are
a few big problems with Monte Carlo,” says Hothersall. “The first problem is
that it’s planning with the autopilot turned on, and that’s not a good way to
plan.”

Monte Carlo simulations came into vogue in the 1960s as computers gained
enough power to compute complex mathematical series. These simulations were
quite different from simple calculations, which were derided for being
one-dimensional, offering just a static view of, say, retirement savings. Monte
Carlo simulations, on the other hand, run thousands or even millions of
scenarios to determine the probabilities for a particular outcome, such as
whether your retirement savings will last through retirement.

Monte Carlo simulations take into account the fact that markets are volatile
and that returns can change from year to year—and even posit strings of bad
years. As a result, Monte Carlo was seen as a giant leap forward in financial
planning. And that reputation grew over the years: in a 2001
BusinessWeek article charting the rising popularity of Monte Carlo
simulations for financial planning, Moshe Arye Milevsky, a finance professor at
York University in Toronto, noted that “in five years, all financial planning
will [be] Monte Carlo.”

But while Monte Carlo simulations offer a more nuanced look at financial
planning than simple calculations, critics such as Hothersall say the
simulations don’t give investors the whole picture. For example, Hothersall
says, financial planning should incorporate a four-legged stool of income,
expenses, taxes, and investments. Monte Carlo, he argues, focuses only on market
returns and ignores the rest. “That’s great if you’re Warren Buffett, but the
rest of us need to focus on the other three legs or the table will collapse,” he
says.

Hothersall contends that investors need planning that takes into account
real-life bumps in the road, from the impact of income taxes to how a part-time
job in retirement will affect Social Security benefits. And what if an investor
retires at age 60, years before Medicare kicks in? Answer: thousands of dollars
annually going toward health insurance premiums—a cost that doesn’t get factored
in by the average retirement planning tool. “Monte Carlo is very quick and easy,
but that’s the problem,” says Hothersall. “They’re trying to fit a complex
situation into a simple model.”

Despite the preponderance of online Monte Carlo-based retirement calculators,
there are plenty of critics who agree with Hothersall that the simulations leave
important information out of their equations. In 2001, David Nawrocki, a finance
professor at Villanova University in Pennsylvania, published his case against
Monte Carlo simulations in the Journal of Financial Planning, noting
that the simulations, at worst, “can lead to incorrect decisions” by investors.
He argues that Monte Carlo simulations are useful in situations where data is
hard or impossible to get. “This is not the case in the investment decisions
typically faced by financial planners,” he writes. “Financial market data is
plentiful and cheap.”

So barring Monte Carlo simulations, where can the typical investor turn to
get a good handle on retirement planning? According to Nawrocki, there are
plenty of analytical models that can be used to give investors a more realistic
picture of their retirement plans. But he says that unless they are math
whizzes, most consumers should leave the number crunching to the experts and get
in touch with a trustworthy financial advisor—like you.