But, I Hated Statistics In School!
Earlier this month, a friend and I approached Chair 11 at the Vail Ski Resort. “Northwoods Express,” as the chair is known, serves a predominantly intermediate section of the mountain all day, and is a high-volume link from the famous back bowls to the village at the end of the day. In a world of high-speed chairs, nothing is ever really a significant wait, but in relative terms, it can get busy here.
A large sign out front announced a planned upgrade for the summer. The current chairlift holding four riders will be replaced by one carrying six. “A capacity upgrade of 25%,” the sign proclaimed. Well, I liked math in school and my friend majored in math before heading to MIT for grad school. So, for the rest of the day, as we worked our way around the mountain, we searched for some way to arrive at a figure of 25% instead of the obvious 50%.
Finally, we placed a call to the former head of mountain operations to see if he could shed some light on this. Was there a different chair spacing planned for the new lift? The answer was no. Was the rope speed going to be slower? Again, the answer was no. Did they assume that there would be frequent stoppage since it is more complicated to move six people into position rather than four? Nope. So, what was it?
“Oh, the guys making the signs don’t really have any idea,” he said. “They just put in a number that sounded good.”
Getting the numbers right as a skier thinking about a chairlift isn’t all that important, after all. But, I suspect many people are about as accurate as the sign makers in terms of numbers and probabilities as they begin to contemplate retirement or some other financial goal.
Future financial returns and future needs are both figures that cannot be predicted with anything approaching certainty. We all laugh about predicting the weather but, in most cases, these forecasts are far better than any guesses made about the direction of the market. And, we do need an educated guess about both returns and needs when we start to set goals and assess whether or not we can achieve them.
Individuals As Insurance Companies
I doubt any of you reading this short essay would have thought of yourself as an insurance company before reading that headline, but hear me out.
In short – both individuals and insurance companies have a series of things they will need to pay for in the future. Neither really knows when those payments need to be made. And, in like manner, both have a series of payments they expect to receive – perhaps with more certainty – but there are many guesses that are being made along the way. The net is their cash flow for any period and, for both, it is highly unclear how much and when any of this will occur.
As an individual or family planning for retirement, for example, there are a number of things we know, or think we know. Here are just a few examples.
• | We know how much money we have today. |
• | We have a viewpoint, perhaps not said out loud, about how much this money might be when we retire. |
• | We should have, but probably don’t have, a viewpoint on how much money we expect to need each year in retirement. |
• | We may have a target year when we “plan” to retire. |
Here’s where the insurance company concept comes in.
• | Insurance companies surely know how much money they have today. |
• | Insurance companies have detailed financial models based on collection of premiums, along with expected market returns with a full set of alternate assumptions. |
• | Insurance companies have a statistical estimation with alternate sensitivity analysis for payments they need to make in the future to policy holders. |
• | Insurance companies have good estimates of when payments will need to be made. |
The real answer reaches back to high school and college. Statistics. “Yuck,” you might say. “I don’t really remember what I learned and I wasn’t all that good when I was in the middle of class.” When people speak with financial advisors, if they are lucky, they will see a presentation of their portfolio run through many scenarios – often called a “Monte Carlo Simulation.”
Churning through estimated returns of each asset class, spending pattern, and health probability by brute force, a graph is often displayed that shows the bulk of the outcomes meeting, beating, or underfunding future needs. After seeing many of these presentations across a variety of firms, I would say the most common response is to flip to the next page and say, “Okay, that looks good.”
But, let’s think back to the late 1990s. At that time, it would have been common for an advisor to sit down and say something like, “Let’s just plug in a market return rate of about 12% and see where you stand.” After all, the go-go 1980s and 1990s would go on forever, right? Well, look back over the past nearly 20 years and those retirees, who planned on 12%, are likely way behind in their ability to live life at the level they were intending.
Over the next months and years, we’ll probably spend a lot more time working through ways to plan better – like an insurance company.
Until the next Daily Pfennig® edition…
Onward and upward!
Sincerely,
Frank Trotter
EVP & Chairman
EverBank Global Markets Group
1.855.813.8484
everbank.com