Dylan McArthur/Globe and Mail
One of the most surprising advances I’ve witnessed in my lifetime is our increasing ability to predict the future. The flawed human prognosticators we relied on back in the day have been replaced by analytics systems that can crunch reams of data and tell us—with shocking accuracy—what’s going to happen tomorrow.
Take the weather forecast. When I was a kid, it was often tragically wrong, especially when predicting rain more than a day or two in advance. Today, jokes about why the weatherman (or woman) always gets it wrong have dried up. Statistics show that today’s three-day weather projections are more accurate than the one-day forecasts were back in the 1980s.
Actuaries, too, have become all-seeing oracles when it comes to our health and longevity. How long you had on this earth used to be one of life’s great mysteries. Now, actuaries use historical data to estimate our lifespans almost to the day.
In fact, it was an actuary who first saw the connection between statistics and health. In the early 1940s, Louis I. Dublin, a vice-president and statistician at the Metropolitan Life Insurance Company, was one of the first to notice that obese people had shorter lives. He developed tables showing the correlation between weight, height and number of years lived that were later used as the basis of the body mass index (BMI).
Dublin’s work was groundbreaking—it set the stage for a whole new approach to public health—but it had limitations. Such models were accurate when predicting the average lifespan for a large group of people, but they didn’t work so well when you applied them to individuals. So while people who drink too much and smoke heavily have, on average, shorter lives, that doesn’t mean that Aunt Sophia, who smokes half a pack of Rothmans for breakfast and washes them down with a mickey of gin, can’t live to 92.
The same limitations hold when we use data to predict which stocks will outperform. In my opinion, only a fool thinks he can divine how an individual stock will fare in the future, no matter how alluring the story behind it. But when you’re talking about groups of stocks, it’s a whole different matter.
Just as people who have certain characteristics are more likely to live longer, stocks that have certain characteristics are more likely to outperform. Norm Rothery, a friend of mine with a PhD in atomic physics and a CFA designation, has devoted much of his career to determining exactly what those characteristics are.
According to Norm, the two key qualities to look for in a stock are a bargain price (as demonstrated by a low price-to-earnings ratio, a low price-to-revenue ratio and other indicators) and upward momentum (stocks that are increasing in price faster than their peers over select time periods). To find such stocks, he subjects all of the companies listed on the TSX to a series of demanding tests, until he is left with just 20.
We introduced Norm’s system in last year’s Top 1000 report, and I’m pleased to announce that his first batch of selected stocks—we call them the Megastars—shot the lights out, chalking up a 16.2% return over a period when the overall market delivered just 2.6%. So we’ve decided to give it another go. You can find a new batch of recommended Megastar stocks in our Top 1000 package.
Norm’s approach has been carefully fine-tuned and tested over time, and I believe it works. I personally use one of his stock-picking systems with my own portfolio. But it’s important to realize that this method doesn’t work all of the time. Follow it faithfully over the long haul, and I predict you’ll be a very happy investor, but there will be the odd year when it disappoints.
That’s because, while the overall group of Megastars should statistically come out on top, there will always be individual stocks in there that buck the odds. For instance, one of last year’s picks, Celestica Inc., crashed by 27%. It met all of Norm’s criteria, but the company, an IBM spinoff that designs and manufactures electronic components for companies like Cisco, is going through a turbulent time, exiting some lines of business and actively looking for mergers and acquisitions.
That makes its future a bit of an enigma right now, no matter what the data says. Sort of like Aunt Sophia, who somehow just turned 93. According to the actuaries, she should be dead, but she lives on, just to spite them.