A 4% Rule Alternative That Won’t Confuse Clients (Much)

What You Need to Know

"Coverage ratios" can illustrate not just whether a retirement income plan is likely to fail but when.
While not a one-and-done metric, this approach can help advisors and clients explore trade-offs in withdrawal planning.

A consensus is emerging among researchers focused on the topic of retirement income planning that simplistic rules of thumb, such as the traditional 4% safe withdrawal rule, are woefully inadequate to guide investors to optimal outcomes in retirement.

At the same time, researchers are also calling into question the usefulness of more sophisticated but potentially equally problematic approaches to managing retirement income — particularly those that rely heavily on binary failure metrics generated by poorly contextualized Monte Carlo simulations, as well as those which rely on solving esoteric utility functions that are more likely to confuse than inform the typical investor.

Against this backdrop, a new analysis published in the Journal of Financial Planning by Javier Estrada of the IESE Business School in Barcelona, Spain, proposes an alternative framework for modeling retirement income that strives to cut something of a middle ground, using a concept known as the “risk-adjusted coverage ratio.”

According to Estrada, when selecting an optimal retirement strategy, a retiree may aim to maximize the coverage ratio, which he calls “a novel metric superior to the failure rate.”

Estrada’s article suggests retirement savers and their advisors focus on the risk-adjusted distribution of coverage ratios while setting up an income plan. Although such an approach may not be as neat as making decisions based on optimizing a single variable, Estrada proposes, it does enable the consideration of the relevant trade-offs a retiree needs to evaluate in order to find an ideal retirement strategy.

Understanding Coverage Ratios

As Estrada writes, there are generally two critical variables that retirees and their financial planners need to consider when deciding an optimal retirement income strategy. These are the initial withdrawal rate and the portfolio’s asset allocation.

“The standard methodology to make these choices properly is to first select a target variable that needs to be maximized or minimized, and then to choose the optimal initial withdrawal rate and asset allocation that solve the optimization problem,” Estrada explains. “Although there is a substantial literature on target variables to be considered, the most typical choice is the failure rate; that is, the proportion of retirement periods in which a strategy failed to sustain a retiree’s planned withdrawals.”

However, as Estrada points out, this approach has two major flaws. It neither distinguishes between a failure early or late in a retirement period, nor does it account for the size and value of any bequest left.

In order to overcome both flaws, Estrada previously introduced the concept of coverage ratios in a 2019 paper (co-authored with MIT’s Mark Kritzman). Put simply, the coverage ratio represents the number of years of withdrawals supported by a strategy relative to the length of the retirement period considered.

Thus, the coverage ratio variable directly takes into account how early or late a strategy fails when it does — and it speaks to the size of the bequest when one is left.

In the earlier paper, Estrada also proposes a utility function that penalizes failures more than it rewards bequests, and he suggests that the optimal strategy is the one that maximizes the expected utility of the coverage ratios across all the retirement periods considered.

As the new paper points out, while selecting an optimal retirement strategy following this approach clearly improves upon selecting the strategy that merely minimizes the failure rate, a potential shortcoming is that retirees are typically not familiar with utility functions.

Hence, Estrada warns, they would not be able to implement the methodology themselves, nor would they likely welcome or even understand their financial planners’ explanation of the underlying approach.

A Better Way

As Estrada writes, one potential solution may be to skip the utility function and simply select the strategy that yields the highest average coverage ratio across all the retirement periods considered, but this alternative may suffer from a typical problem with averages.

“Just like the [proverbial] individual that drowned crossing a river four feet deep on average, a high average coverage ratio may be hiding many periods in which a strategy failed, which are compensated by a few periods in which the strategy left very large bequests,” Estrada explains.

As such, the approach proposed in the new article, besides avoiding utility functions, also avoids focusing on just one average number. In fact, Estrada’s suggestion is to focus on the whole distribution of coverage ratios, or at least on some relevant percentiles of such a distribution.

“Doing so would enable a retiree to carefully consider not just the mean or median coverage ratio but also the coverage ratios that may happen with a low probability, particularly on the left tail of the distribution,” Estrada argues, referring to scenarios in which the strategy fails. “Clearly, this approach is not as neat as selecting a strategy that maximizes or minimizes the value of a target variable, but it does enable retirees to consider likely (average) scenarios and unlikely (positive or negative) scenarios, as well as to weigh them according to their individual preferences.”

Quirks in the Analysis

The new paper runs through a number of theoretical examples in an attempt to demonstrate how the coverage ratio framework can be used to make decisions about both portfolio allocations and withdrawal rates. In basic terms, a given client can identify their preferred coverage ratio and then, in essence, mix and match their portfolio allocation and withdrawal plans accordingly.

Estrada takes pains to show that this method, while coming along with some key advantages, also has its shortcomings. For example, he notes that, “unsurprisingly, the mean and median coverage ratio increase monotonically with the allocation to stocks in the portfolio.”

“This may seem to suggest that a retiree should select a very aggressive (or the most aggressive) asset allocation, but an important insight of the approach proposed here is that such a limited analysis may be misleading,” he warns. “It is conceivable … that a high mean or median coverage ratio may stem from, say, 49% of the retirement periods in which a strategy depleted a portfolio in year three, and 51% of the retirement periods in which a strategy left a bequest equal to 60 years of withdrawals.”

As Estrada emphasizes, the mean and median coverage ratios in a given analysis can mask what most retirees would consider an unacceptably high failure rate.

“In other words, the mean or median coverage ratios for a strategy may not be enough, and may even be a misleading way to properly select an ideal retirement strategy,” Estrada warns. “Additional information provided by the distribution of coverage ratios should also be considered.”

Estrada further notes that, although it is typically the case that gains and losses of the same size imply asymmetric pain and gain (with the former being roughly twice as large as the latter), the upside potential of different strategies is far from irrelevant.

“Hence, a retiree may also consider unlikely but positive scenarios, such as those indicated by coverage ratios in the 90%, 95%, or 99% percentiles on the right tail of the distribution,” he explains. “Importantly, although the failure rate suffers from the flaws already discussed, it is neither irrelevant nor likely to be ignored by retirees.”

Takeaways for Financial Planners

Estrada says the approach proposed in his paper can easily be used by financial planners to advise retirees on how to select an ideal retirement strategy.

“As previously discussed, focusing just on the mean and median coverage ratio of different strategies is likely to be insufficient and perhaps even misleading,” Estrada writes. “For this reason, planners would help retirees greatly if they discussed other percentiles of the distribution, focusing on those more important to each retiree.”

Some retirees may be very risk averse and focus on bad scenarios, however unlikely, in which case planners can discuss the coverage ratios expected with low probability of negative outcomes.

“Furthermore, the fact that all the coverage ratios … monotonically decrease (and the failure rate monotonically increases) as the initial withdrawal rate increases does not necessarily imply that retirees should choose a very low initial withdrawal,” Estrada notes.

To illustrate this fact, Estrada considers a retiree whose overriding goal is to find a strategy that sustains their planned withdrawals during retirement, and their secondary goal is leaving a bequest.

“ln that case, a planner should highlight that [decreasing the initial withdrawal rate] would not necessarily make the retiree better off,” he explains. “The initial withdrawal rate beyond that point will inflict on them a marginal cost (foregoing a more comfortable retirement) higher than the marginal benefit they obtain (leaving a larger bequest).”

Put differently, the approach would enable planners to incorporate retirees’ preferences in the selection of an ideal strategy, but without having to specify (and explain) a utility function.

“In short, the approach proposed here, although clearly not as neat as selecting the strategy that maximizes or minimizes the value of a target variable, provides retirees and their financial planners with enough information and flexibility to evaluate all the trade-offs they may consider relevant,” Estrada concludes. “Furthermore, rather than dealing with utility functions, which most individuals do not know or understand, the methodology advanced here enables planners to discuss with their clients the likely and unlikely scenarios deemed to be more relevant, and to weight them according to their clients’ preferences.”