By Stephanie Richman, CFP
As a financial advisor, I’ve had the pleasure of helping many clients comfortably reach and enjoy their retirement years. During my career, a few consistent themes have emerged. Clients generally want to know if their money will last their lifetime, or they have a good idea that it will but want to validate those assumptions. They may also be curious about how else the money could potentially be deployed, such as for traveling, buying a second home, or making monetary gifts during their retirement years.
Good financial advisors can help answer all of these questions. An important tool at our disposal is Monte Carlo analysis, which assesses the mathematical probability that individuals will meet their goals. In the process, the simulations can help reassure those planning for retirement to stay the course through market ups and downs so that they are more likely to achieve their goals.
Over the past two decades, a few stretches have certainly tested clients’ confidence — the dot-com bubble of 2000-2002, the financial crisis in 2008-09 and last year’s severe market downturn due to the coronavirus. Part of my job as an advisor is to help people maintain perspective, so they can persevere through difficult economic times by thinking long term. Monte Carlo simulations assist in this endeavor by testing variable outputs, i.e., testing your unique situation under varying market conditions.
Monte Carlo Methodology
Monte Carlo simulations utilize market indices to represent the components of a portfolio, while factoring in income, expenses, and life expectancy. Each simulation then picks a random starting point between 1926 and the end of the previous calendar year. The methodology runs a thousand simulations to determine if a person’s money would last through different market conditions, taking into account various asset class returns, inflation, standard deviation, market volatility, etc. In the process, very poor market conditions such as the Great Depression of the 1930s are accounted for, along with very strong conditions such as the prolonged bull market of the 2010s.
As a complement to the simulations, it’s important to note that during the period from 1945 to 2009, the average contraction was only about 11 months while the average expansion was about 58 months. Last year, especially, many clients were confused by the performance of the market. They asked me how it could make such a dramatic recovery following the steep downturn in March and April, when there continued to be so much bad economic news related to the pandemic.
The answer is that markets tend to discount the future. According to data from Strategas Research Partners, from July 1953 to June 2009, the average market recovery started four months before the official end of the corresponding recession. Additionally, the average market return from that low point to recession end was 24.9%.
Through financial services websites, investors may find calculation tools that incorporate Monte Carlo simulations. But being able to see the numbers is only half the battle, and an important way that financial advisors can add value is by making sense of all that data. The resulting impact can be immense.
Another appealing aspect of Monte Carlo simulations is how they can offer insight into whether a certain action would be sensible or not. One example is gifting to children or grandchildren, perhaps for educational purposes. Here, an individual may like the idea of seeing the benefit of that gift during their lifetime versus only bequeathing money upon their passing.
In these cases, we can conduct scenario planning such as testing whether a client could afford to gift a certain amount to their grandchildren every year until each grandchild turns 18. Monte Carlo simulations show how a person’s long-term plan would fare with and without that gifting, helping them to make an informed decision.
In my experience with clients, simulations have also played an important role for those looking to move when they retire. For example, one couple was planning to move to Oregon from the San Francisco Bay Area. Having a specific town picked out, they told me the average cost of homes there and asked about affordability, as well as whether a mortgage or outright purchase might make more sense.
We were able to factor those variables into Monte Carlo simulations and determine that they’d be successful either way; however, choosing a mortgage would be a better option. By choosing to take out a mortgage, more of their liquid assets would remain invested to potentially generate more money via asset growth to enjoy in retirement or leave to heirs.
Monte Carlo simulations may also help shed light on sequence-of-returns risk, which is the danger that the timing of withdrawals from a retirement account can negatively impact the returns it will generate over time. This can be more pronounced if you begin retirement in a bear market. Using a simple illustration, picture taking monthly withdrawals from your portfolio. When the market is up, there is not too much concern, but when you take withdrawals when the market is down, you’re likely to sell more shares to take the same income. This leaves fewer shares to move up when the market recovers. In short, withdrawals hurt an account’s long-term ability to provide returns more if they are made during a down market versus an up market. Monte Carlo simulations stress test various sets of returns so you can see how your asset allocation may impact how long your portfolio may last.
In the scenario of buying a new home, utilizing a mortgage can be a better option than paying outright because a large amount withdrawn early in retirement can negatively impact a portfolio’s longevity. In other words, with a mortgage, the purchaser wouldn’t be taking as much money out of liquid assets early in retirement. So even though interest must be paid on the mortgage, the market’s performance may outweigh those payments and generate greater assets.
Applying sequence-of-returns risk to this concept, if money is taken out of the market early in a person’s retirement years to spend on a house, it doesn’t have the opportunity to stay invested, compound and possibly provide greater flexibility and liquidity over time.
Painting a Picture
In conclusion, a picture is worth a thousand words. As an advisor, I could talk all day about whether a client is likely to retire successfully but being able to show them through the use of Monte Carlo analysis has an almost magical effect.
It’s so powerful when people can see all of their relevant financial information on one page, enabling them to uncover how their cash flow is likely to look each year for the rest of their lives. The opportunity to make such an amazing impact is why I love what I do.
About the author: Stephanie Richman, CFP®, CPCC®
Stephanie Richman, CFP®, CPCC®, is Regional Director of Northern California/East Bay at EP Wealth Advisors, in the firm’s Lafayette, California, office. In her role, she is resolved to promote a superior level of client service, while overseeing cohesive teams in the firm’s Northern California region and working to extend the firm’s growth strategy. Stephanie is passionate about financial planning and has expertise in retirement planning as well as estate planning.