Monte Carlo: Take The Gamble Out Of Divorce Settlements

Your first thought when hearing the words “Monte Carlo” might be of the lively Las Vegas strip, a swift roll of the dice, or colorful slot machines.

While that may be the more exciting meaning, ‘Monte Carlo’ is also a powerful financial tool. Specifically, the Monte Carlo we are talking about here is a statistical model that illustrates how decisions you make today are likely to impact your finances decades into the future.

Robert Powell, CFP^®, an entrepreneur and columnist, once notably said “Monte Carlo offers you the opportunity to be approximately right, rather than exactly wrong.”

Given how little control you may feel that you have in a divorce, getting things directionally right is a huge success. Using Monte Carlo can give you confidence that you’ve negotiated a strong settlement or confidence that the benefits of continuing to negotiate might outweigh the total price–the time, energy, and “life” costs in addition to the money paid.

Monte Carlo In General Financial Planning

In financial planning, Monte Carlo is a barometer that tells us how likely someone is to be able to help achieve their goals without having to make adjustments.

Monte Carlo projections rely on key financial assumptions, including:

• Current age and estimated mortality
• State of residence for income tax purposes
• Desired retirement age
• Desired spending in retirement
• Investable assets and cost basis of taxable assets
• Current and future income

Here’s a hypothetical example: A 55-year-old has $3 million of investable assets today, wants to spend $200,000 annually in retirement, and wants to know at what age they can retire and not have to worry about running out of money.

You could simply run a “straight-line projection,” where you assume that the investment portfolio will provide the same average rate of return every year and evaluate how many years of spending can be accomplished before running out of money.

A straight-line projection assumes a fixed annual return, calculating how long your savings will last. But markets don’t work that way. Some years your portfolio makes money and others it loses money—at least on paper.

Additionally, it is rare for an investor’s return to match the average. For instance, if we assume the average long-term rate of return for a portfolio comprised of 60% stocks and 40% bonds is 6%, the most likely scenario is that an investor would experience a variety of annual returns scattered around 6%, without seeing an annual return of 6% very often.

It’s kind of like the weather: While the actual temperature on a given day is typically within a reasonable range of the historical average, it’s rare that the actual temperature is the historical average for that specific day, and there are years when the temperature is 20 degrees above or below the average.

Instead of assuming a stable rate of return each year, Monte Carlo uses randomized annual returns based on a range of historical returns and risk data to better reflect reality. When Monte Carlo is used, some years, the portfolio return will exceed the annual average, and other years, it will be less than the market average.

For our hypothetical 55-year-old, the first five years of the projection might look like this:

Straight Line:

Year 1: 6%

Year 2: 6%

Year 3: 6%

Year 4: 6%

Year 5: 6%

Monte Carlo:

Year 1: 11%

Year 2: -15%

Year 3: 7%

Year 4: 18%

Year 5: -3%

Another layer to Monte Carlo is that the projection is typically run 1,000 different times with randomized market returns and different timing of those returns included in each scenario. This provides a “stress test” of the projection and the Monte Carlo simulation then produces a probability of success. Most commonly, success is defined as having a high likelihood that no adjustments would be needed to current spending or saving assumptions from now until estimated mortality.

Monte Carlo In Divorce Decision Making

Monte Carlo can be immensely helpful in evaluating divorce settlement proposals. Throughout the process, there are so many decisions that need to be made. Most people have a hard time seeing the forest from the trees. Monte Carlo simulations can help provide clarity on what life can look like post-divorce.

There are various ways to model scenarios, however, common complexities explored are:

• The financial impact of a proposed property split
• Comparing a buyout versus annual support payments
• Options in settlement of significant non-marital assets
• Keeping the marital home
• Affordability of purchasing or keeping a second home
• Ability to provide discretionary support to young adult children
• Determining a travel budget
• Necessity for growth and risk in the investment portfolio
• Most tax-efficient strategies for philanthropy and legacy goals

If you use Monte Carlo projections, it is important that you have a basic understanding of the inputs and assumptions. The most common concern with Monte Carlo simulations is the quality of the inputs. This ranges from reasonable portfolio returns and inflation assumptions, to realistic spending amounts. Inputs can be subjective, but you want to ensure detailed research has been done to use the most accurate assumptions possible.

Working with a family law attorney and a Corient wealth advisor ensures that your projections are based on realistic, defensible assumptions—helping you secure a stronger financial future.

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