Journal of Financial Planning: September 2012
Jerry A. Miccolis, CFA, CFP®, FCAS, is a principal and the chief investment officer at Brinton Eaton, a wealth management firm in Madison, New Jersey, and a portfolio manager for The Giralda Fund. He co-wrote Asset Allocation For Dummies® (Wiley 2009) and numerous works on enterprise risk management. (miccolis@brintoneaton.com)
Marina Goodman, CFP®, is an investment strategist at Brinton Eaton and a portfolio manager for The Giralda Fund. She has been working to bridge the gap between research and practice to improve the portfolio optimization process. (goodman@brintoneaton.com)
The financial planning literature has seen a flurry of recent research into the safe withdrawal rate (SWR). The SWR is the maximum initial percentage of a client’s invested assets that can be spent as a constant standard of living (resulting in a dollar amount that is subsequently inflation-adjusted regardless of market performance) without running out of money when tested over any historical market scenario. Such thought leaders as Bengen, Guyton, Pfau, Kitces, and others have made, and continue to make, great contributions to this field of study, some in this very publication.
While there is not much debate that the generic SWR in this country is in the neighborhood, and perhaps a bit north, of 4 percent, the focus of more current research has been on ever-more-finely customizing the results to individual client circumstances. We applaud these efforts, even though we believe that client-specific variables lead to an inescapable truth: in evaluating whether a client can sustain his lifestyle throughout the rest of his life (or, equivalently, in determining the maximum level of a sustainable lifestyle), there is no substitute for from-the-ground-up, client-centric analysis, periodically updated. There are simply too many variables unique to each client to give us any faith that a universal measure such as SWR, however customized after the fact, can hope to do justice to any one client.
The good news for advisers who share this view is that the excellent research and development that has marked much of the study of SWRs has natural and immediate application to the client-specific analyses we planners do.
Lifetime Cash-Flow Projections
Most planners use some version of a lifetime cash-flow projection (LCP), with Monte Carlo simulation, to evaluate the viability of each of their clients’ financial plans. These LCPs capture lots of key information particular to the client, such as age; retirement objectives; tax situation; risk tolerance; investment strategy; multiple sources of income; fixed, inflation-sensitive, and one-time living expenses; charitable inclinations; gifting/estate intentions; liquidity needs; etc. The LCP is a very powerful planning tool, and one that resonates well with clients. But there are numerous features that can be enhanced.
For the most part, LCPs use a single metric to gauge the success of the overall financial plan—the probability that the client will never run out of assets, or what some planners call a “confidence level.” The time horizon of the projection is usually a fixed number of years, to age 95 or 100 for example, that is comfortably beyond the client’s life expectancy. And the assumption is that the client’s lifestyle, and any changes to it, are specified in advance. The conceptual advances in approach that SWR studies have introduced in recent years provide a blueprint for us to make each of these LCP features more flexible and realistic.
Enhancement #1: More Completely Measuring Success
One takeaway from much of the SWR research is that there is a variety of ways to measure success, and each is quite relevant. So, a clear improvement is to supplement the single confidence-level metric built into most LCPs with a multi-dimensional view. One of these additional dimensions is to capture not just the probability of shortfall (the complement of the confidence level) but the severity of the shortfall as well. A shortfall that could easily be rectified in a year or two is much different for planning purposes than one that the client has no hope of making up for in her remaining lifetime.
Another dimension is to capture the ending level of wealth, or “legacy size” of each simulation. Some clients will assign a higher priority to leaving a legacy than will others. The broader point is that your simulation results contain a very rich set of information, and focusing on a one-dimensional metric throws a lot of that information away. A typical client may view success as some combination of high confidence level, low shortfall severity, and high legacy size. Some researchers have suggested measuring how the client would weight each of these metrics by means of a client-specific “utility function.” However they are achieved, these enhancements get us closer to how our clients actually think about the risks inherent in their financial future.
Enhancement #2: Realistically Reflecting Longevity
No one can predict a given client’s remaining life span. In light of this, we tend to estimate the planning horizon on the long side, to be conservative. In the work of several SWR researchers, successive-year survival probabilities at each age of the client’s life are estimated. So, a second enhancement that suggests itself is to replace the fixed planning horizon with a stochastic one that reflects the client’s age at each point in the simulation. In effect, simulate a range of horizons while you’re simulating a range of annual investment returns, etc., based on readily available mortality tables. This would represent a more realistic view than simply assuming every client’s finances need to survive to a common fixed age, no matter the client or the simulation set.
As a practical matter, this would help planners avoid the situation of asking their clients to cut back on their lifestyle for the rest of their lives solely because they are assuming the worst-case longevity scenario of living to age 100. Be careful here, however. We have found that, left to their own devices, clients tend to routinely underestimate their longevity, so showing results at a few specific advanced ages would be useful as well.
Enhancement #3: Recognizing Client Optionality
Clients have choices. We should, accordingly, allow the LCP model to incorporate rules-based decision making by the client as events play out. In real life, clients can exercise prudence by, say, cutting back on discretionary spending when times are lean. In the LCP, you can have a rule to do just that when simulated investment results generate a prolonged downturn. Including such client options will automatically make financial plans more successful, all else equal, and this is simply reflecting reality. Just as incorporating options in their planning allows corporations to undertake ventures they would not embark on otherwise, adding this feature allows us planners to accurately assess whether our clients can pursue fuller lifestyles than they otherwise would.
In our view, it is a matter of time before these enhancements become routine features of standard LCP software. We can thank our SWR researchers for that.
What’s All This Have to Do with Investing?
This is an investment column, after all. What’s the connection? There are several.
First, there are metrics in common use in investment management that would have immediate use in financial planning. For example, the conditional value at risk (CVaR) metric that we referenced in our Journal article “Next Generation Investment Risk Management: Putting the ‘Modern’ Back in Modern Portfolio Theory” (January 2012) is a perfect choice for measuring shortfall severity within the LCP. And the literature on efficient portfolio construction has many references to using utility functions that capture and combine multiple metrics in the same sense that we mentioned above.
Second, the LCP, suitably enhanced, provides a very effective and objective tool to evaluate the use of single-premium fixed annuities as an investment to help clients immunize their financial futures. In particular, the LCP approach is tailor-made to help planners judge the trade-off between risk reduction and legacy shrinkage that these annuities present.
Third, most planners use the LCP to, among other things, help clients decide on an overall investment strategy. For example, once all the other assumptions are reasonably nailed down, you can run the client’s LCP through a range of investment scenarios, each of which represents a particular “investment path” that the client might follow throughout his life. One such path might begin with a moderate/aggressive investment strategy in pre-retirement, and gradually migrate to a more conservative strategy with advancing age. Another path might be just the opposite, as unconventional as it might seem (but that we have found relevant for some younger clients facing big-ticket expenses early in their future).
The “optimal” path is the one that gives the client the most desirable combination of confidence level, shortfall severity, and legacy size. This is an easily doable and fairly low-tech approach. But we can see this being continually enhanced over the years toward the ideal of creating a dynamic, rules-based investment path that is fashioned entirely around each client’s specific cash-flow needs.