There is no absolutely foolproof way to predict what will happen in the future. But running a Monte Carlo simulation that allows for the real possibility of disaster can give you a clearer picture of how much money you can safely withdraw from your retirement savings.

Here's how the Monte Carlo method works and how it can be applied it to your retirement planning. It's also important to understand where it can fall short and how to correct for that.

Key Takeaways

  • A Monte Carlo simulation can be used to test if you will have enough income throughout your retirement years. 
  • Unlike a traditional retirement calculator, the Monte Carlo method incorporates a variety of variables to test possible retirement portfolio outcomes.
  • Critics of this method claim that it can underestimate major market crashes, but there are ways to remedy this flaw.

Understanding the Monte Carlo Simulation

The city of Monte Carlo in the country of Monaco has long served as a playground for the jet set. At its famous casino, rich gamblers come to play for high stakes in games of random chance where strategy and experience can provide little or no benefit. The Monte Carlo simulation is a mathematical model used for risk assessment named after this gambling mecca.

People who are trying to plan for a secure retirement and can't afford to lose their savings don't want to take big chances with their money. So why would they turn to a Monte Carlo scenario for guidance?

Although choosing this name for the calculation may seem ironic, it is a planning technique used to calculate the percentage probability of specific scenarios that are based upon a set group of assumptions and standard deviations. The Monte Carlo method has often been used in investment and retirement planning to project the likelihood of achieving financial or retirement goals and whether or not a retiree will have enough income to live on for life, given a wide range of possible outcomes in the markets.

While there are no absolute parameters for this type of projection, the underlying assumptions for these calculations typically include such factors as interest rates, the client's age and projected time to retirement, the amount of the investment portfolio that is spent or withdrawn each year, and the portfolio allocation. The computer model then runs hundreds or thousands of possible outcomes using actual historical financial data.

The results of this analysis usually come in the form of a bell curve. The middle part of the curve delineates the scenarios that are statistically and historically the most likely to happen; the ends—or tails—measure the diminishing likelihood of the more extreme scenarios that could also occur.

Limitations to Consider

Despite its apparently thorough mathematical breakdown of possible future outcomes, market turbulence has served to expose a major weakness that seems to afflict this method of financial projection. Supporters are quick to point out that Monte Carlo simulations generally provide much more realistic scenarios than simple projections that assume a given rate of return on capital.

The probability scenarios produced by Monte Carlo simulations can help give you a clearer picture of risk, such as whether or not you will outlive your retirement savings.

But critics contend that Monte Carlo analysis cannot accurately factor infrequent but radical events, such as market crashes, into its probability analysis. Many investors and professionals who used this method were not shown a real possibility of market performance, such as during a financial crisis, according to research.

In his paper, "The Retirement Calculator from Hell," William Bernstein clearly illustrates this shortcoming. He uses an example of a series of coin tosses to prove his point, where heads equals a market gain of 30% and tails represents a loss of 10%.

  • If you start with a $1 million portfolio and toss the coin once a year for 30 years, you will end up with an average annual total return of 8.17% over that time. That means that you could withdraw $81,700 per year for 30 years before exhausting your principal.
  • If you were to flip tails every year for the first 15 years, however, you would only be able to withdraw $18,600 per year. But if you were lucky enough to flip heads the first 15 times, you could take out a whopping $248,600.

And while the odds of flipping either heads or tails 15 times in a row seems statistically remote, Bernstein further proves his point using a hypothetical illustration based on a $1 million portfolio that was invested in five different combinations of large and small cap stocks and five-year Treasuries back in 1966. That year marked the beginning of a 17-year stretch of zero market gains when you factor in inflation.

History shows that the money would have been exhausted in less than 15 years at the mathematically-based average withdrawal rate of $81,700. In fact, withdrawals had to be cut in half before the money lasted for the full 30 years.

How to Plan Realistically

There are a few basic adjustments that experts suggest can help remedy the shortcomings of the Monte Carlo projections. The first is to simply add on a flat increase to the possibility of financial failure that the numbers show, such as 10% or 20%.

Another is to plot out projections that use a percentage of assets each year instead of a set dollar amount, which will greatly reduce the possibility of running out of principal.

The Bottom Line

The Monte Carlo simulation can be used as part of a toolbox to help plan for retirement. It predicts different outcomes that will affect how much it is safe to withdraw from your retirement savings over a given period of time.

It’s not without drawbacks. Critics contend that it can underestimate major bear markets. Experts, however, suggest a few ways to overcome the shortcomings of the model.

You can take the method for a spin via numerous online tools including one offered by Flexible Retirement Planner, which is free, or by consulting with a financial advisor.