Thursday, February 23, 2017

The Actuarial Approach and the Importance of Ongoing Financial Planning

Many financial advisors utilize Monte Carlo analysis (MCA) to help their clients develop financial plans in retirement.  We have written in the past about the potential problems of using MCA, and frankly we are not big fans of relying on it exclusively.  The Actuarial Approach that we advocate utilizes transparent deterministic assumptions and anticipates ongoing (generally annual) valuations of a retiree’s assets and liabilities to help keep a retiree’s spending on track throughout retirement.  Because it does not use MCA and appears to be more volatile than the approach they use, the Actuarial Approach is looked upon by many academics and financial advisors as somehow inferior. This post will once again:
  • attempt to defend the approach we advocate as just as good, if not better than MCA, and 
  • encourage individuals and their financial advisors to consider using the Actuarial Approach for financial planning, at a minimum as another data point to be considered in the spending decision process.
The inspiration for this post was a recent Michael Kitces’ blog post written by Derek Tharp, which set forth steps financial advisors can take to avoid having their clients misinterpret their MCAs.  We agree with Mr. Tharp that there are several potential problems with MCAs and some of these problems can be mitigated if financial advisors:
  • stress that “Clients should understand planning is not a one-time occurrence”, 
  • “Emphasize the importance of ongoing planning”, and 
  • “Present information in more than one way.”

We believe financial planning is a process that benefits from periodic attention.  As pension actuaries in our former lives, we performed annual actuarial valuations to determine annual contribution ranges for our plan sponsor clients.  Like the process anticipated by the Actuarial Approach, the pension contribution determination process involved periodic measurements of assets and liabilities, along with deterministic assumptions about the future.  We and our clients both knew that the assumptions we made about the future in a pension actuarial valuation would not be exactly realized in subsequent years, and the plan’s future annual contribution ranges would change somewhat from year to year as actual experience emerged.

This pension actuarial process was not then and is not now a “set and forget” process.  We did not, as a general rule, do a MCA with 10,000 simulations of the future, tell our clients that keeping this year’s contribution level and the current asset mix fixed in future years had a 92.3% probability of successfully funding the plan for the indefinite future, and leave it at that.  It was understood that there would be ongoing valuations and changes to keep the plan’s funding on track.  The client also understood that there was considerable contribution flexibility built into the process, as the impact of future experience deviations and changes in assumptions on future contribution ranges could be smoothed to some degree.  It is with this same “deterministic assumption and annual valuation process” background that we approach personal financial planning.

Monte Carlo Analysis

Monte Carlo analysis (or Monte Carlo modeling) attempts to forecast the future based on historical experience.  This is somewhat analogous to trying to drive a car while looking out the back window.  There is an excellent likelihood that future experience won’t be anything like prior experience, and the projection will be inaccurate.  Running 10,000 simulations does not improve one’s ability to forecast the future.  Under MCAs used by many financial advisors, historical real rates of return and probability distributions of returns for various asset classes are assumed to continue.  For the client, MCA is a non-transparent process that requires a fair amount of faith.

To make these projections somewhat more realistic, some financial advisors adjust historical returns to reflect current economic conditions.  Since the primary output of a MCA is a probability of success for a given level of real dollar spending, there is an implication, if the probability of success is high enough, that the resulting spending level is essentially guaranteed and need never be changed. To achieve this result, the analysis assumes not only that historical returns will repeat themselves, but that the client will spend exactly the specified real dollar spending budget each and every year in the future.  Mr. Tharp is correct that clients may be easily mislead by MCAs.  What the clients do know is that MCAs involve lots of sophisticated calculations, so they figure they must be right.

Monte Carlo Analysis vs. the Actuarial Approach

By comparison, the Actuarial Approach (utilizing recommended assumptions) assumes future deterministic investment returns based on current insurance company annuity pricing.  These investment return assumptions are independent of the client’s actual investment strategy.  If the client’s actual future investment returns deviate from this assumed rate, the assumed rate is changed or if actual spending deviates from the spending budget, the client’s future actuarially determined spending budget will increase or decrease accordingly.  This does not imply, however, that the client’s spending must fluctuate from year to year, as the client’s annual spending budget (or actual spending) can be smoothed to some degree.

It has been our experience that an initial spending budget for a retiree who desires a relatively high probably of success under a well-conceived MCA approach that properly recognizes all sources of income and all significant expenses, is generally comparable to the spending budget developed under the Actuarial Approach with recommended assumptions.  In fact, the Actuarial Approach may produce higher initial spending budgets than the MCA approach under these circumstances.  It has also been our experience that initial spending budgets developed using adjusted historical experience and high probabilities of success don’t vary greatly based on the client’s asset mix, as the higher expected returns expected from mixes containing more equities are mostly counterbalanced by the larger amount of risk in such investment portfolios.

While initial spending budgets developed by the two approaches may be comparable under certain circumstances, the Actuarial Approach offers several features that are not generally available under a traditional MCA:

  • It allows one to easily model investment risk and spending risk.  Our workbooks contain a 5-year projection tab that gives the client the opportunity to model the effect on future actuarial spending budgets of deviations in future investment returns and spending.  This type of information can be helpful in developing investment strategy and general financial planning. 
  • It allows one to model different future spending patterns.  Unlike MCAs which typically assume constant real dollar future spending, our workbooks permit the user to assume declining real dollar future spending more consistent with observed spending in retirement.  The budget by expense-type tab in the ABC for Retirees also permits the user to make different increase assumptions for different types of future expected expenses.

Monte Carlo Analysis and the Actuarial Approach Can Work Together

If the MCA properly considers all the client’s assets and future expenses/liabilities, uses reasonable assumptions about the future, and the client is comfortable with a given probability of success and constant real dollar spending in retirement, the MCA approach may produce a reasonable spending budget for the client.  As Mr. Tharp says in his article, however, it is important for clients to recognize that developing a spending budget is not a one-time event and should be revisited periodically.  In addition to reflecting actual investment performance and actual spending, the client’s spending budget may also change over time as the client’s spending goals change.  We believe the data points obtained by applying the Actuarial Approach on an annual basis can:

  1. Be an independent check on the reasonableness of a Monte Carlo analysis, 
  2. Be an important supplement to the data points developed by a MCA in keeping client spending on track and consistent with the client’s financial objectives, and 
  3. Present information in a different way to increase client understanding.
Therefore, we encourage retirees and their financial advisors to periodically compare the spending budgets they develop with their MCAs (or other approaches) with spending budgets under the Actuarial Approach.

We like the way Mr. Tharp thinks, and we look forward to future articles by him.  In a future blog post, we will discuss how Mr. Tharp’s post of February 22 regarding development of spending budgets that are expected to decline in real-dollars as retirees age is yet another advertisement for using the Actuarial Approach.