Another Way to Calculate How Much Clients Can Spend in Retirement

Chance are that pretty much any financial advisor working with pre-retirees and retired clients will be very familiar with the use of Monte Carlo simulations, which are commonly used to assess an individual’s probability of running out of money once their income from work ceases.

According to retirement planning expert and researcher Derek Tharp, however, many financial advisors and their clients fail to appreciate the limitations of Monte Carlo simulations — especially the limitations associated with running just one analysis at the start of the client’s retirement period and using this as the basis for all future spending decisions.

Most significantly, Tharp says, the traditional “success versus failure” framing fails to capture the reality that retirees, when facing an unlucky sequence-of-returns scenario that could result in their running out of money, can and often do make adjustments to their spending that allow them to avoid that unfortunate outcome.

Ultimately, Tharp says, the superior way to help retired clients avoid both over-spending and under-spending is to constantly update and revisit their spending plan. Doing so will mean leveraging many ongoing Monte Carlo simulations that can help a given individual set upper and lower guardrails on spending and risk-taking.

While this approach will demand more effort from the advisor, it will almost certainly result in superior outcomes for clients, Tharp says.

Tharp makes this case on the latest episode of Morningstar’s The Long View podcast, hosted by Christine Benz and Jeff Ptak. During a nearly hour-long discussion with the Morningstar experts, Tharp also explains why he is drawn to the retirement income planning topic, both as a practicing financial advisor and as a researcher.

Simply put, Tharp says, the effort of seeing a client (or a research subject) through the retirement period is one of the most intellectually challenging and rewarding parts of his job. As such, he encourages fellow industry professionals to consider their own planning process and whether they can improve their approach to the “decumulation challenge.”

The Problem With Single-Simulation Planning

According to Tharp, financial advisors working with retirement clients very often use Monte Carlo simulations in their financial planning process. Typically, they utilize financial planning software packages that generate projections in terms of probability of success or failure.

Broadly speaking, success is defined as an iteration of the plan where the client doesn’t run out of money, Tharp explains, while failure naturally signifies the opposite. Often, plans are considered acceptable if the probability of success is near 90%.

Tharp says these analyses are an incredibly important part of the planning process, but they are also at significant risk of being misinterpreted. This is especially the case when a financial advisor simply runs one Monte Carlo analysis at the beginning of the retirement period and fails to consider whether ongoing reviews of the spending plan are in order.

Most significantly, the single success-or-failure framing fails to capture the reality that retirees, when facing an unlucky market scenario, can and often do make adjustments to their spending that allow them to avoid financial failure.

According to Tharp, to better reflect this reality, the phrase “probability of adjustment” has emerged as a commonly suggested alternative to “probability of success.” While representing an improvement over the original, Tharp says, “probability of adjustment” itself can be prone to ambiguity and misinterpretation without being clear about what type of adjustment might be needed — and what the outcome might be if that adjustment weren’t made.