Let me deal with the necessary disclosures and disclaimers first: I am a huge fan of Moshe Milevsky, professor at York University in Toronto, prolific author and insightful analyst about retirement planning matters and my colleague here at Research magazine. It is not excessive to state that he is the world’s leading authority on retirement income strategies. I am not unbiased and will not pretend to be unbiased. That said, Prof. Milevsky’s new book, The 7 Most Important Equations for Your Retirement (Wiley) is a terrific read. In it he tells stories of the lives and work of the people and the ideas supporting retirement income planning today.
That Prof. Milevsky uses stories (and a light, breezy tone) is significant because we love stories. They help us to explain, understand and interpret the world around us. They also give us a frame of reference we can use to remember the concepts we take them to represent. Perhaps most significantly, we inherently prefer narrative to data—often to the detriment of our understanding because, unfortunately, our stories are so often steeped in error.
In the context of financial planning, as elsewhere, we all like to think that we carefully gather and evaluate facts and data before coming to our conclusions and telling our stories. But typically we don’t.
Instead, we tend to suffer from confirmation bias and thus reach a conclusion first. Only thereafter do we gather facts, but even so tend to do so to support our preconceived conclusions. We then take our selected “facts” and cram them into our desired narratives, because narratives are so crucial to how we make sense of reality. Keeping one’s analysis and interpretation of the facts reasonably objective—since analysis and interpretation are required for data to be actionable—is really hard even in the best of circumstances.
Nassim Taleb calls our tendency to create false and/or unsupported stories in an effort to legitimize our preconceived notions the “narrative fallacy.” That fallacy threatens our analysis and judgment constantly. Therefore, while we may enjoy the stories and even be aided by them, we should put our faith only in the actual data, especially because they are so often in conflict. Thus our interpretations of the data need to be reevaluated constantly.
As mathematician John Allen Paulos noted in The New York Times last fall: “There is a tension between stories and statistics, and one under-appreciated contrast between them is simply the mindset with which we approach them. In listening to stories we tend to suspend disbelief in order to be entertained, whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled.”
It is delightfully ironic, then, that Prof. Milevsky—a quant if ever there was one—uses the stories behind the great retirement income equations to bring home the importance of the data. Prof. Milevsky describes how Leonardo Fibonacci—best known for spreading the use of Arabic numbers to Europe and popularizing what came to be known as the Fibonacci sequence—ascertained present value and provided the math for calculating how long one’s retirement nest egg could be expected to last while earning a fixed amount on that money and making fixed withdrawals from it. We learn that how to value an income annuity was figured out by Edmond Halley, a comet-chasing (yes—Halley’s Comet) astronomer, following his father’s suspicious death and a plot to kill the King of England.
Prof. Milevsky tells us how famous British actuary (to the extent that’s not a contradiction in terms) Benjamin Gompertz discovered and formulated the first natural law of human mortality nearly two centuries ago. Gompertz discovered that the mortality rate for populations increases by an average of about 9% per year. Therefore, if a given population has a 10% chance of dying at age 65, the survivors will have about a 10.9% chance of dying at age 66 and those survivors will have about an 11.8% chance of dying at age 67, and so on, until the pattern breaks down at very advanced ages.
We also meet Dr. Solomon Huebner, Wharton’s charismatic “father of insurance education.” Huebner brought the tools of economics and human capital valuation to the life insurance industry, providing discipline and respect to a disparaged industry. His key discovery relates to human life value—the present value of wages, salary and income someone earns over a working life, which can and should be insured in the same way property is insured; this allowed life insurance to become an important financial planning tool. He even demonstrated how to calculate the present value of a life insurance policy.
Prof. Milevsky introduces us to Irving Fisher (who provided the foundation for life-cycle finance), to Paul Samuelson (who recognized that a longer time horizon doesn’t diversify risk away and scolded a young Prof. Milevsky for publishing a paper claiming otherwise, inspiring him to do better) and, finally, to the Soviet mathematical prodigy Andrei Nikolaevich Kolmogorov. Kolmogorov advanced many fields, but Prof. Milevsky focuses upon an algorithm that can be used to provide a one-number summary that quantifies the sustainability of a retirement plan.
As told by Prof. Milevsky, the stories of these seven men and the equations supporting their work are interesting and fun. He even concludes with a poem about the stories and individuals in the book written by his 11 year-old daughter. But they are much more than entertaining.
Bear Stearns won a famous 2002 litigation involving former Fed Governor and Bear Chief Economist Wayne Angell over advice he and the firm gave to a client (colorfully) named Count Henryk de Kwiatkowski after the Count lost hundreds of millions of dollars following that advice. The jury awarded a huge verdict to the Count but the appellate court reversed, holding that brokers cannot be liable for honest opinions that turn out to be wrong when providing advice on non-discretionary accounts.
What is significant for our purposes was a line of testimony offered at trial by then-Bear CEO Jimmy Cayne. Cayne apparently thought that Bear could be in trouble so he took a creative and disarmingly honest position given how aggressive Bear was in promoting Angell’s alleged expertise. Cayne brazenly asserted that Angell was merely an “entertainer” whose advice should never give rise to liability.
Economists are right only 35-40% of the time, Cayne testified. “They don’t really have a good record as far as predicting the future,” he said. “I think that it is entertainment, but he probably doesn’t think it is” (and I doubt that the Count was much amused). “I don’t know how he spends most of his time,” asserted Cayne. “He travels a lot and visits people and has lunches and dinners and he is an entertainer.”
In an odd sense, Cayne was precisely if hypocritically correct in that instance. There is nothing wrong with using or being assisted by a good story. But stories aren’t facts and should never be treated and relied upon as such, entertaining as they often are.
Happily for us, Prof. Milevsky uses good, entertaining stories—designed to lead to good conversations—to provide practical (and accurate!) building blocks to help us think carefully and critically about life, money and retirement. In this telling, the equations, the data and the stories all align to provide the critical foundation necessary for important decisions to be made about retirement income planning and the future. I highly encourage you to read The 7 Most Important Equations for Your Retirement.
Bob Seawright is chief investment and information officer for Madison Avenue Securities in San Diego.