Courtesy of Calvin Wiersma, CFP®, MST, Financial Advisor at Grand Wealth Management
How can you measure progress when your destination is uncertain? A few years ago, I was driving to Acadia National Park, a national park that I had never been to before. It was about midnight, and I was looking forward to setting up my tent and going to sleep. One thing stood in my way: finding my campsite through unfamiliar terrain.
The uncertainty of financial planning can be like finding your way through unfamiliar terrain. Uncertainty makes progress difficult to measure. Building a financial plan that will be sustainable despite all the uncertainty of life can be daunting. However, just as I relied on a map, road signs, and the compass in my car to find my campsite, there are indicators that can show that a financial plan is on the right track—even if the future turns out differently than anticipated.
Monte Carlo Analysis
One of our important tools is called Monte Carlo analysis. Monte Carlo analysis in financial planning software is a common measurement of a financial plan’s probability of success (Hopewell 1997). It calculates thousands of market return scenarios and comes up with a statistical probability that a financial plan will be successful. For example, a Monte Carlo analysis result may show that a financial plan has an 85% probability of success. This means two things: first, there is about an 85% chance that no changes will have to be made to the financial plan to be successful; and second, about 15% of the outcomes indicate a change to spending or saving would have to be made to get the plan back on track.
Even though it’s not possible to know in advance whether your financial plan will be successful, using a Monte Carlo analysis is a good indicator for if the financial plan is on the right track, like landmarks along your route. When evaluating a financial plan, a Monte Carlo probability of success of about 75% or above is a good place to start.
Measuring Pace by Withdrawal Rates
Another approach used by savvy investors is varying their withdrawal rate. The withdrawal rate is the percentage of the portfolio that is spent annually during retirement, traditionally around 4%. In 1994, William Bengen’s research demonstrated that a diversified portfolio could sustain a 4% withdrawal rate for a 30-year period (Bengen, 1994). Choosing a sustainable withdrawal rate increases the chances that a financial plan will be a success, even if small changes are required along the way.
Over the years, additional research has shown that a safe withdrawal rate could be higher than 4% (Pfau 2017). Jonathan Guyton and others have conducted research that shows the annual withdrawal rate for a retiree with a higher allocation to stocks and who is willing to be flexible with their spending could sustain a 5.5% withdrawal rate annually (Guyton, Klinger 2006). The nuance that Guyton included was a set of rules called Guardrails that modeled how someone might change their spending in response to market performance. The Guardrail rules change spending based on the portfolio value and increases or decreases the withdrawal rate to maintain a sustainable path. If the withdrawal rate exceeds the set threshold, a financial planner can help their clients decrease spending to ensure that the portfolio can support future spending needs. The opposite is true if investment returns are higher than expected. The same rules apply, and the withdrawal rate is increased. An indicator that shows if a financial plan is on the right pace is a valuable tool in the hands of a wise investor so that a change can be made before it is too late!
Back to Reality
Monte Carlo analysis and monitoring withdrawal rates may prepare you to make long-range plans for your future, yet you may be asking how this applies to your everyday life now. An important step to building a financial plan is to plan for spending that meets reality by setting realistic goals with your financial planner. For example, a financial plan with a high probability of success would hardly work in real life if that plan called for extreme changes in spending each year.
Often, retirees have flexibility to reduce living expenses by small amounts every so often, meaning they can probably forgo a vacation or occasionally reduce charitable giving. For others it may not be practical to reduce spending that much, for a variety of reasons. If you have less flexibility to reduce spending, starting with a lower initial withdrawal rate may lead to fewer decreases in spending in the future.
It is natural for spending to ebb and flow. As retirees grow older, their spending typically decreases in the middle years of retirement before increasing at the end. David Blanchett calls this the Retirement Spending Smile (Blanchett 2014). It is important to keep this in mind because it will naturally help retirees keep their spending on a sustainable path. Starting with the appropriate level of spending helps to balance doing the things that matter most in life and preserving what you need for the future.
Conclusion
Using Monte Carlo analysis, withdrawal rates, and real spending analysis, a financial planner can help you create a good measurement of your financial plan. Each measurement compliments the others. They show whether the current plan is sustainable, if changes have to be made down the road, and if the plan is realistic. Even when it feels like the destination is unknown, these clues along the way can create confidence to go forward doing the things that matter most instead of worrying about getting lost in the dark.
Sources: Bengen, William P. 1994. “Determining Withdrawal Rates Using Historical Data.” Journal of Financial Planning 17 (3): 172–180; Blanchett, David. 2014. “Exploring the Retirement Consumption Puzzles.” Journal of Financial Planning 27 (5): 34-42; Case, K., Quigley, J., & Shiller, R. 2013. “Wealth effects revisited: 1975-2012.” http://doi.org/10.3386/w18667; Guyton, Jonathan, Klinger, William. 2006. “Decision Rules and Maximum Withdrawal Rates” Journal of Financial Planning 19 (4): 50-58; Hopewell, Lynn. 1997. “Making Decisions Under Conditions of Uncertainty” Journal of Financial Planning; Pfau, W.D. 2017. How Much Can I Spend in Retirement?: A guide to investment-based retirement income strategies. Retirement Researcher Media; Tharp, Derrick. 2017. “Does Monte Carlo Analysis Actually Overstate Tail Risk in Retirement Analysis?” https://www.kitces.com/blog/monte-carlo-analysis-risk-fat-tails-vs-safe-withdrawal-rates-rolling-historical-returns/