How do you know if you have enough? It’s a question most of us have contemplated and, if we haven’t, it is worth consideration. In this note we propose a reasonable method to answer the unanswerable, but with a lot of footnotes.
Though an inexact science, there is much to be learned from the process of evaluating your retirement income plan. It helps ensure the right questions are addressed and a realistic and workable plan is developed.
When it comes to our retirement income how much is the right amount, and how do we conceptualize the notion with assets invested in the financial markets?
We have found most investors appreciate knowing if they are on the path to achieving their goals. That said, it is difficult to pin down “enough” as both life itself and market returns are uncertain. We have a pretty good idea about what the really long-run looks like – e.g., the equity markets will be up and we’ll be dead – but it isn’t very practical for income planning.
So how do we address the reality of the uncertainty we face? Each one of us will only experience one retirement, but there are many ways it can play out. Given what we expect about future returns, we can “imagine” thousands of different ways your retirement could unfold. So that is what we do. We simulate the various ways it could materialize, with each simulation being a standalone “retirement” you may experience.
For several reasons, we focus on the most important risk – that is, the risk of outliving your investment nest egg. This is more important than paying unwarranted attention to the political or economic fiasco du jour. The process provides an opportunity to assess the likelihood of meeting your goals when operating in a world with many unpredictable variables. Modeling the future is a complex undertaking, but whether you have enough is not an equation to be solved. There are simply too many unknowns.
As far as financial markets, what happens when stocks do very well then suffer? What about when stocks suffer immediately and then recover? What happens if bonds perform poorly? What happens if the length of the expansion or downturn defies logic?
Including ourselves further complicates the equation. We typically become accustomed to a certain standard of living and, therefore, we can make assumptions about future withdrawals. However, what is the effect when life requires we spend more than expected or we live longer than we could have imagined? Rather, how is our nest egg affected when these inevitabilities transpire amid the inexorable market fluctuations?
To develop the various “retirements” we could experience, we start with a set of reasonable assumptions about the long-term and run thousands of simulations, each representing a full retirement period. The process develops a probability distribution about our chances of success, given our expectations regarding financial market returns, contributions, withdrawals, time horizon, and asset allocation.
In developing and evaluating the many possible “futures” with all their moving, interconnected, and unknown variables we can develop some degree of confidence that we have enough. If we do not have enough, the exercise provides productive feedback as to what we can do given what is within our control.
Assumptions will turn out to be false, of course – we don’t know what the world will look like in 30 years. But the takeaway is that at any given time it is helpful to know where we stand with respect to our broad goals.
An income plan is more like a compass than a map; it is a tool to provide direction rather than a prescriptive path for the future. Let us know if we can help with your retirement income projection, or if this topic generates any ideas for future notes.
We are always here to help.
Contact us at 865-584-1850 or email@example.com
 This is not entirely true. But only considering the long-run ignores sequence of return risk.
 In one scenario the market performs well in the beginning of your retirement and poorly at the end, for example. Conceptually, there are an infinite number of “retirements” you could experience.
 The statistical process is known as a Monte Carlo Simulation (MCS) and, employed in the context of wealth management, models financial market returns, addressing sequence of return risk and path dependency issues.
 Running thousands of simulations does not change the fact that we only experience one retirement. Thus, to be effective the process ought to be iterative.