As households and financial advisors increasingly use Monte Carlo planning tools to help determine saving and spending in retirement, it’s important to take a step back and make sure the key underlying assumptions are valid.
One area that I think needs to be improved in Monte Carlo tools today is the most common outcomes metric, which is typically the probability of success. Success rates can often paint a misleading picture about the implications of accomplishing a goal because they do not provide any perspective on the shortfall if the goal is not accomplished (in its entirety). This is especially for financial goals like funding retirement, given the notable duration (lasting 30+ years), since most Americans have lifetime income sources (e.g., Social Security retirement benefits), as well as underlying flexibility associated with spending, which makes adjustments a lot less harmful than suggested by “failure.”
Goal completion, which is the percentage of a goal the individual accomplishes (versus treating the outcome as binary), is an alternative outcomes metric that I think should be more widely considered. Using goal completion can have a significant impact on retirement guidance, which is something I’ve demonstrated in research, for readers who want to dig into this more!
The Monte Carlo Movement
Monte Carlo projections have become an incredibly common way to incorporate uncertainty into financial planning forecasts today. A key differentiator with a Monte Carlo projection versus other projection methodologies (e.g., time value of money calculations) is the element of chance (i.e., randomness). While returns are typically the only assumed random variable in most financial planning Monte Carlo tools, other variables could be randomized as well (e.g., age of death, age of retirement, a health shock, etc.).
“The binary nature of success rates isn’t consistent with how people typically approach financial goals.”
David Blanchett
When it comes to translating the results of a given Monte Carlo projection into a single statistic the “probability of success” has emerged as the overwhelming favorite. The success rate is estimated by counting the total number of trials (or runs) the respective goal is accomplished (e.g., retirement income) divided by the total number of trials. For example, if a retiree wants $50,000 a year for 30 years, the success rate would be the number of runs in the projection the retiree accomplishes this spending goal, divided by the total number of runs.
A significant flaw in the success rate calculation is that it ignores the extent of a shortfall if the goal is not accomplished in its entirety (i.e., the magnitude of failure). For example, falling $1 short in the 30th year of a projection with $50,000 would be treated as failure, despite the fact the person would have accomplished 99.99%+ of his or her (or their) goal.
The binary nature of success rates (pass/fail) isn’t consistent with how people typically approach financial goals. For example, if a retiree is off track, he or she will likely make an adjustment to spending. This adjustment could be relatively minor (slightly cutting back at later years) or potentially more significant (a more notable cutback), but the nature of the potential adjustment is not communicated when using outcomes metrics like the probability of success.
I think outcomes metrics that focus on “goal completion” provide a more useful context around how well (or poorly) someone is likely to accomplish a goal. Goal completion can be estimated in a variety of ways, but the simplest approach is to estimate what percentage of the goal is accomplished. This approach effectively communicates the potential magnitude of a shortfall and can often provide a very different perspective than success rates.
This effect is demonstrated in the next exhibit, which includes a hypothetical projection consisting of ten runs where the goal is to generate $100 per year. We can see that in five of the ten runs the individual does not accomplish their goal, resulting in a 50% success rate; however, he accomplishes 96% of the goal, on average.
Success Rates vs Goal Completion as Outcomes Metrics
This is a notably different way to contrast potential outcomes. Would a retiree be willing to accept a 50% success rate? Probably not. Would a retiree be willing to accomplish 96% of a goal, on average? That seems a lot more likely.
Conclusions
Most financial goals are not pass/fail, especially in retirement. The continued focus on success rates in the financial planning industry is likely to result in households and financial advisors making suboptimal decisions in a variety of domains, such as portfolio risk levels, retirement spending levels, and allocations to lifetime income. Moving towards more realistic outcomes metrics, like goal completion, would be a relatively low lift for many existing financial planning tools, and would provide significantly better guidance in the future.
DISCLOSURES
All investing involves risk. The views expressed herein are those of PGIM investment professionals at the time the comments were made and may not be reflective of their current opinions and are subject to change without notice. Neither the information contained herein nor any opinion expressed shall be construed to constitute an offer to sell or a solicitation to buy any security.
David Blanchett, PhD, CFA, CFP, is Managing Director and Head of Retirement Research, DC Solutions for PGIM, the global investment management business of Prudential Financial, Inc. In this role, he develops research and innovative solutions to help improve retirement outcomes for investors. He is also an Adjunct Professor of Wealth Management at The American College of Financial Services and a Research Fellow at the Alliance for Lifetime Income.
