How to Use Monte Carlo Simulations for Retirement Planning
Running these simulations can boost your odds of success in retirement
A Monte Carlo simulation is like a stress test for your financial future. Using financial planning software and retirement calculators, you can leverage these powerful forecasting models in your retirement planning if you understand how to use them and interpret their results.
What Is a Monte Carlo Simulation?
Unlike traditional forecasting models that make estimates based on static variables, this dynamic forecasting model named after the casino hub of the same name in Monaco offers a means of testing the outcome of a process over a range of possible variables to account for the inherent risk and uncertainty of that process.
Although the model has been used in fields ranging from economics to finance, it has widely been used in retirement planning to predict the likelihood that investors will have a particular level of retirement income through life expectancy.
To accomplish this, the model tests the probability that your nest egg will last through retirement by considering various variables. Monte Carlo simulations for retirement involve these five variables at a minimum:
- Portfolio size: This is the value of your retirement savings.
- Portfolio allocation: This is the percentage of stocks, bonds, and cash that make up the portfolio.
- Annual income to be withdrawn: This is the amount you plan to take out of your retirement accounts to fund your living expenses.
- Annual deposits: This is the amount you plan to add to savings until retirement.
- Inflation: This is the rate of inflation applied to the income withdrawn.
- Time horizon: This is the number of years you have until retirement.
When you run one of these simulations, you can modify any of the above variables, along with others, to see how it affects the likelihood of sustaining your income throughout retirement.
How Monte Carlo Simulations Aid in Retirement Planning
Many investors assume that they can forecast their retirement nest egg based on a consistent average rate of return. But the reality is that you don't know what your future portfolio returns will be. Looking at historical data, returns for stocks and bonds can vary widely over 20-year return time periods.
If you assume a consistent rate of return, your retirement nest egg may fall short of your needs if the market experiences an unforeseen downturn and you do not have time to recover your losses. In contrast, if the market performs much better than you expected during certain periods, you may unnecessarily underspend your nest egg, in some cases to the point that you can't live comfortably.
In addition, given the possible variations in the variables used in the simulation, you can follow the same allocation approach as another retiree who plans to stop working at the same time as you intend to and still experience a completely different outcome, even though you make identical choices. This is referred to as sequence risk.
In contrast, Monte Carlo simulations for retirement use actual historic data and standard deviations to factor in potential market fluctuations and test your income outcomes over a wide combination of possible market returns. They typically deliver an answer in terms of your probability of success based on the total number of internal simulations that are run, which can range from hundreds to tens of thousands depending on the simulator. If, for example, your retirement income survives in 4,000 of 5,000 scenarios, that scenario would be 80% successful. The goal in retirement is to have a high probability of success.
Most financial planning software used by professionals incorporates some type of Monte Carlo simulation. In addition, popular Monte Carlo financial planning software and retirement calculators for consumers, such as Retirement Simulation and Vanguard's Retirement Calculator, rely on Monte Carlo simulations to provide investors a better sense of their success in retirement than average annual rates of return.
Using the Simulations to Calculate Your Retirement Nest Egg
The free financial planning application Retirement Simulation allows you to get your feet wet and learn how to interpret simulations. It incorporates past rates of return and inflation along with variables beyond the norm, such as an unforeseen stock market collapse, to forecast your chances of success in retirement.
Assume the following variables:
- Current age: 40
- Retirement age: 67
- Current savings: $300,000
- Annual deposits: $5,000
- Annual withdrawals: $40,000
- Stock market crash: none
- Portfolio: 60% stocks, 40% bonds
The results indicate that this person has an 89% chance of success of having his inflation-adjusted nest egg last until age 102 and a 99% chance of success of sustaining his income until age 78.
However, let's assume that the stock market declines by 40% at age 55. Run the simulation with the crash, and the probabilities reduce to 80% and 98% at age 102 and 78, respectively.
What about the 20% of the time where the plan fails at age 102? The simulation assumes that this individual makes no changes to his lifestyle and keeps on spending the same amount of money. However, if you recognize that probability of failure is increasing because of variables you can control—the age at which you start withdrawals, or the annual withdrawals or deposits, for example—you can change these variables in life to reduce the number of failure scenarios and the overall failure rate. Play with different variables and look for opportunities to boost your odds of success and reduce the odds of an income shortfall in retirement.
When using Monte Carlo simulation, run simulations with both likely scenarios and "what-if" scenarios, such as a stock market crash, to get a more accurate sense of the possible portfolio you will have to draw from in retirement.
Final Thoughts on Monte Carlo Simulations
Using financial planning software and retirement planners that use this unique forecasting model can provide a better indication of your financial security in retirement than relying on average annual rates of returns alone.
However, it's based on assumptions and is not a guarantee of success. There's no surefire way to predict whether the market will perform as it did in any of the simulations. In addition, a divorce, the onset of a disability, the death of the primary income provider, or another serious personal financial impact can substantially reduce the odds of retirement success that are spit out by these simulations.
For all their strengths, Monte Carlo simulations are still based on assumptions that may not bear out in the future.
One way to offset overly favorable assumptions is to factor in multiple what-if scenarios, such as stock market collapses or below-average returns or above-average rates of inflation. In addition, if you encounter a poor set of economic circumstances in your early retirement years, adjust the variables that are your control to ensure that a failure scenario does not occur or that the rate does not increase. Much like with many financial situations, identifying problems early gives you time to remedy them and stretch your nest egg further.