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Margin of Safety

Richard Connor  |  October 28, 2020

MANY FINANCIAL planners say they “stress test” portfolios. That sounds like a good idea, but it isn’t well defined. I decided to do some research to see how I could apply the notion to the investments owned by my wife and me.

I came across a number of useful articles. Investopedia, one of my go-to resources for all things financial, provides this definition: “Stress testing is a computer simulation technique used to test the resilience of institutions and investment portfolios against possible future financial situations.” Forbes, meanwhile, provides a three-step process that I thought was useful.

Among financial planners, two common approaches are historical data analysis and Monte Carlo simulations. The historical approach uses past asset class returns to analyze how a portfolio would have fared historically. The idea: If your portfolio survived the past ups and downs of the financial markets, you’ll probably be okay in future.

The Monte Carlo method is similar, but takes the idea even further. It’s a mathematical method that starts with historical asset class returns for, say, each calendar year and then, over and over again, assumes these annual returns occur in a different order. This results in hundreds or even thousands of different possible scenarios, allowing you to develop a statistical distribution that shows how your portfolio might perform.

Monte Carlo simulations are especially useful for looking at whether folks will have enough money for retirement, given the amount they plan to withdraw each year from their portfolio and the range of potential returns. One big worry: Retirees get hit with atrocious returns early in retirement and those returns, coupled with their own spending, eviscerates their portfolio.

I think both the historical approach and Monte Carlo analysis are useful exercises, and they can help boost confidence in a retirement plan. But both also assume that the future will be at least somewhat like the past. What if that’s a bad assumption? That’s why I’ve added a margin of safety to our retirement plan.

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How do you do that? I’m aware of three key strategies. First, you could assume your living expenses will be higher than is likely. This gives you a buffer if your portfolio doesn’t grow as expected. In fact, some planners assume spending starts high, but declines as their clients age. I’ve observed that in my parents and in-laws. But you probably shouldn’t bank on this happening. Increased medical and long-term-care expenses could kick in as your retirement progresses, so your net spending may not shrink—and it could grow.

Second, you could assume low investment returns. For instance, if your portfolio can support your lifestyle through a long retirement, even if your investment returns simply match inflation, that should make you more confident.

Finally, you might add a margin of safety by assuming you’ll need to spend down your nest egg over a very long life. I run my scenarios through to age 100. The financial planners I know worry a lot about longevity. Many folks, however, seem to be more concerned with dying young and “leaving money on the table.” This attitude often drives them to claim Social Security early. The downside: That means a permanently reduced monthly benefit and hence a weaker retirement safety net.

My engineering training tells me to do a little bit of everything—assume a higher cost of living, low investment returns and a long retirement. After all, you don’t know what or where the anomalies will show up. Can you overdo this? Sure, you could provide so much margin for safety that you live too frugally and deny yourself some well-deserved retirement fun. Still, I wouldn’t cut it too close.

Richard Connor is a semi-retired aerospace engineer with a keen interest in finance. Rick enjoys a wide variety of other interests, including chasing grandkids, space, sports, travel, winemaking and reading. His previous articles include State of TaxationParadise Lost and Much Appreciated. Follow Rick on Twitter @RConnor609.

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