How RIAs use Monte Carlo simulations to help clients

A statistical analysis of random outcomes

Talking about investing in gambling terms is generally frowned upon. So it may seem ironic that a common financial modeling technique is named after the famous casino in Monaco. Monte Carlo simulations are likely so named because they focus on the statistical analysis of chance and random outcomes. They’re utilized by many RIAs to examine different investment strategies to determine which is mostly likely to help their clients achieve their financial goals.

“It gives you a way of determining if your portfolio is constructed correctly,” says Robert Stammers, an investment professional, thought leader and a former executive at the CFA Institute.

A Monte Carlo simulation assumes that the annual returns for various investments are not certain. In other words, returns will vary each year within a given range. Usually, the advisors who use the simulation software rely on historical data to determine how much annual variability there will be in the analysis. Analysts can also vary the allocation of different assets to compare different investment strategies.

“The idea is to get a probability analysis of [the output] of those scenarios,” Stammers says.

The results show the likelihood of various investment outcomes and the probability of them achieving the client’s financial goals.

Garbage in, garbage out with Monte Carlo analysis

“People use this technique in retirement planning to figure out what their retirement [could] look like,” Stammers says. It helps them determine the likelihood they will have saved enough money.

Executing a meaningful Monte Carlo analysis requires financial and economic savvy. Specifically, if the data and assumptions entered into the model aren’t realistic, then the results won’t provide a meaningful insight. “It’s garbage in, garbage out,” Stammers adds. “If you put in bad information — like bad probabilities, if your expectations are bad — then you’ll get bad outputs.”

That raises another issue: how to identify the appropriate data and assumptions. These can include forecasts of future stock returns, inflation rates and interest rates. Even veteran Wall Street professionals can find it challenging to make forecasts in this field. Selecting appropriate variables requires the specialized skills of an experienced analyst.

Those who do possess such skills use their knowledge and experience to make changes to the Monte Carlo inputs. They base those adjustments on fluctuating market circumstances and the economy’s health. In this way, the results of the simulation may reflect reasonable assumptions and are more likely to be useful.

A key variable used in Monte Carlo analysis for investors is the value of stocks relative to their earnings — the price-to-earnings ratio. Based on this metric, some financial analysts might forecast lower future stock returns when stock values are relatively higher. They might also increase their expected stock returns when valuations look low. “We go into the software, and we adjust forward returns based on a valuation metric,” says Richard Rosso, director of financial planning at RIA Advisors.

Making adjustments when the outlook changes

Rosso’s company conducts its own asset class research. This helps ensure that the Monte Carlo simulations use reasonable assumptions for an entire portfolio. Notably, at the height of the COVID-19 pandemic in 2020, he raised his forecast for inflation long before the maker of the Monte Carlo software he uses did. “My thought was inflation was going to stick around, so we had a committee meeting and we adjusted it,” he says.

Inflation forecasts are vital in financial modeling because they typically influence interest rates. In turn, when interest rates rise or fall, the value of stocks and bonds typically changes also. Making reasonable investing assumptions is important because clients rely on the forecasts they receive from RIAs, Rosso adds.

The consequences of overestimating future portfolio gains can lead to unintended changes to a client’s lifestyle and difficult conversations. Put simply, Rosso doesn’t want to tell someone they are able to retire and then five years later tell them they need to get a job. “That’s a discussion I really don’t want to have,” he says.