NEW YORK (InvestorSolutions)—Place one hand on a hot stove, and the other on a slab of dry ice. Any statistician will tell you that on average, you are comfortable–but, of course, you know it’s not so. The markets’ average returns hide very long periods of both very weak and very strong performance. What’s more, averages are derived from past returns, but future returns are unlikely to exactly mirror the past. Naively relying on “average” numbers without considering the market’s wide variations can lead to disaster.
The models we use to describe market behavior become critical to our retirement planning. We often say that stock prices follow a random walk, in which each price change is independent of the one that preceded it. But studies have shown that there is more serial correlation than a random distribution would predict. In other words, both winners and losers repeat more often than they should. We also typically say that stock-market returns are normally distributed, but actually there are far more very good and very bad periods than there should be if market returns mapped out as a true bell-shaped curve; the “tails,” as they are called, are too fat.
For instance, based on the average daily market volatility of the preceding 50 years, the crash of 1987 should happen just once in 55 million years. (A statistician would say that the crash was a 16 sigma event, or outside of 16 standard deviations from the average.) So, investors can all go back to sleep, right? Well, not quite. It would be foolish to build a plan that didn’t take into account at least one more good crash during our lifetimes.
Getting more and bigger winners than you should is not catastrophic. But what if the losers are bigger and more often than we expect? How might that affect the plan? And if some of those big losses show up during the first few years of retirement, will you be able to recover?