Long-time readers of our blog know that we aren’t big fans of Monte Carlo models generally used by financial advisors for financial planning. These models typically use historical investment return assumptions (or other assumptions that may not be clearly communicated to the clients) in simulations to produce what financial advisors claim to be probabilities of being able to spend $X per year in retirement. Of course, these probabilities are only as good as the assumptions used in the simulations and can change significantly as actual experience emerges (such as the actual investment returns experienced this year). You may wish to revisit our post of January 29, 2021 to read a discussion of the significant limitations of Monte Carlo models typically used today.
Many retired households do not desire to be significant risk-takers when it comes to their retirement spending. When given a choice, they choose to be more conservative and will frequently choose a Monte Carlo generated plan that they believe (or hope) will have a 90% or better chance of succeeding. Of course, there is no guarantee that past experience used in Monte Carlo models will be duplicated in the future. Therefore, personal financial thought-leaders like Michael Kitces are trying to convince financial advisors (and their clients) to adopt changes to their Monte Carlo modelling approaches to make them more like the Actuarial Financial Planner. For more discussion of Mr. Kitces’ Risk-Based Guardrails Model, see our post of November 28, 2021 and the latest Kitces.com post of June 29, 2022.
We understand why many retirees want to be reasonably conservative when it comes to their retirement plans, particularly with respect to their essential spending. This is why our AFP incorporates basic actuarial principles and a Safety-First Investment Approach, matching non-risky investments with expected essential spending during retirement. We also recommend assuming a longer-than-life-expectancy lifetime planning period.
In this post, we will discuss how you can relatively easily make the spending budget developed using the AFP even more conservative (or less conservative) if you want. We discuss how you can develop a spending budget range by varying some of the assumptions or inputs so that you can select a spending budget within the range that is consistent with your personal tolerance for risk.
Developing a spending budget range using the AFP
The easiest way to develop a spending budget range using the AFP is to override the default assumptions to make them more conservative or more aggressive. For example, you could use the following approach to develop Optimistic, Intermediate and Pessimistic scenarios similar to the approach employed by Social Security actuaries for developing the range of financial status results summarized in the annual OASDI Trustees reports.
Possible Assumptions to Generate a Reasonable Range of Spending Budgets
Assumption | More Optimistic | Intermediate (Default) | More Pessimistic |
Floor Portfolio Nominal Investment Return | 4.5% | 4.5% | 4.5% |
Upside Portfolio Nominal Investment Return | 8.5% | 7.5% | 6.5% |
Inflation | 2.5% | 3.5% | 4.5% |
Floor Portfolio Real Investment Return | 2% | 1% | 0% |
Upside Portfolio Real Investment Return | 6% | 4% | 2% |
Lifetime Planning Periods | Default assumptions -5 years | Actuaries Longevity Illustrator--25% Probability of Survival for healthy non-smokers | Default assumptions +5 years |
You could also vary input amounts for expected long-term care expenses, unexpected expenses, future social security amounts, etc. for each of the scenarios.
In addition to varying the lifetime planning periods, the above table reflects three different sets of assumptions for real investment returns (nominal return less inflation) expected on non-risky and risky assets. The real returns expected on non-risky assets are 2% for the More Optimistic scenario, 1% for the Intermediate scenario and 0% for the More Pessimistic scenario
After inputting the alternative override assumptions in the AFP, you would:
- Rebalance your non-risky/risky investments to fully fund your revised Floor Portfolio, and
- Solve for the spending budget for each scenario that produces approximately the same Rainy-Day fund as the Intermediate scenario.
This is a much simpler process to produce a reasonable range of spending budgets than Monte Carlo modeling as it does not involve hundreds or thousand of simulations of future experience, but it still provides a reasonable indication of how conservative or aggressive your spending budget may be.
Social Security real rate of return assumptions for range scenarios.
To give you a sense of real rate of return assumptions for non-risky assets assumed for other purposes, lets look at the ultimate assumptions for returns on OASDI Trust Fund assets (after an initial 10-year period) used by the Social Security Trustees and actuaries. The table below shows the ultimate nominal and real rates of return assumed in the 2022 Trustees’ Report.
Low-Cost Scenario | Intermediate Scenario | Hi-Cost Scenario | |
Nominal Investment Return | 5.8% | 4.7% | 3.6% |
Inflation | 3% | 2.4% | 1.8% |
Real Investment Return | 2.8% | 2.3% | 1.8% |
This table shows that the ultimate real investment return assumptions for the special issue government securities held in the Trust used in the 2022 OASDI report are generally higher than those we recommend for non-risky investments used to fund Floor Portfolios. However, when comparing these assumptions, you should keep in mind that
- Assumed real rates for the next ten years for OASDI are less than the ultimate rates shown in the above table
- Social Security actuaries select rates for the next 75 years, where households generally need to select rates for no more than thirty or forty years, and
- Assumed real rates of return for Social Security are not as critical as they are for households since the relative size of program assets to program liabilities is much smaller.
Summary
The AFP is a relatively simple, but powerful, actuarial tool that you can use to help you plan for retirement. In our opinion, it has significant advantages over the Monte Carlo models used by most financial advisors. By varying the transparent assumptions used in the calculations (using the AFP override feature) and following the process outlined above, you can develop a range of spending budgets that can help you decide just how conservative or aggressive you really want your plan to be.
