Before I begin my discussion of smart beta, I want to briefly pay tribute to a soon-to-be relic from my past. For many who live near the border of North and South Carolina, Independence Day includes a trip to the Carowinds theme park for a day of thrills and fireworks. With that in mind, I wanted to give a tip of the hat to the grand old roller coaster Thunder Road, whose time is unfortunately up. Perhaps the wooden structure hasn’t been thrilling visitors like the park’s newest addition, the Fury 325, the world’s tallest and fastest coaster. However, I will certainly miss it.
Back when the kids were young, we purchased season passes to the park every year. The best part of having season passes is that we could run up after work for a few hours on a weekday. One of our favorite rides was Thunder Road. Unlike the Fury 325, old Thunder Road traveled a mere 45 miles per hour. Instead of smooth and fast, she bucked, shook, and rattled over the rails. To increase the fun, a simple seat restraint was used, but it wasn’t quite tight enough to hold you firmly in place. During those weeknights we could ride once, twice, or as many times as we wanted, as we rarely had to wait in line between rides. What fun it was for all.
As we look back over the past six months, the ride in the world of investing is a lot like the ride given by Thunder Road. The economy, interest rates, stock prices, the dollar, gas prices and just about everything else shook, rattled, and bucked around, but ended just about where they started on January 1st. I wish it was as fun as those days with my kids on the coaster, but it wasn’t, as you know.
We have mentioned many times that when prices for common stocks are at or above our calculation of fair value, forward returns will depend on growth in earnings, dividends, and the general level of interest rates. All of these change slowly. As we see it today, forward returns for the rest of the year should be positive, but less than we are used to. Of course, anything could happen when prices are not at bargain levels, including some thrilling shakes, rattles, and rolls. An old sage used to warn me to “buckle up,” for we are in for a good ride. You can be assured that we have tightened the seat belt in hopes that it will hold us in place.
Now, on to “smart beta.” The phrase sounds as though it must refer to something special. After all, every one of us wants to be a “smart” investor. As for the word “beta,” it sounds smart on its own. Combine the two words, add a great marketing team, and you are sure to capture a few dollars from investors who believe you can outsmart the market and reap better than average returns. And wouldn’t that be nice? Earning better than average returns over time would assure that each of us could easily have more than enough money to meet any goal we may have.
Over the years, I have become quite skeptical of any claims of easy outperformance, and smart beta is no exception. Without going into mathematical equations, we can explain beta using an example. Take the size of your home. If your home is 3000 square feet, and your neighbor’s home is 1500 square feet, you know that your house is twice as large as your neighbor’s. At the same time, if you know that the average house in your community is 1500 square feet, you know that your house is twice the size as the average house in your community. Beta measures the volatility of one investment to the volatility of the average investment. It is the same as comparing the square feet of your house to the average square feet of the houses in your community. If the beta of one investment is high relative to the average investment, it would be considered riskier, or more volatile than the average of all investments. If the beta is low relative to the average, it would be considered less risky, or less volatile than the average of all investments. To simplify the measuring, in math, the beta of the average is always equal to 1. If an investment has a beta of 2.0 it would be twice as risky as the average of all investments. If the beta is 0.50 it would be one-half as risky as the average.
I guess now, simply because we have some idea of what beta is, we can claim to be smart, and if we use that knowledge to make better than average returns, I guess we can claim to be “really smart!” Smart beta is more or less a marketing term. In application, it represents a form of factor investing. A factor such as price to book, price to earnings, dividend yield, or one of the multitude of individual stock characteristics is studied to see how a portfolio which owns a number of companies with the same factor has performed relative to the entire market. If one of these characteristics produces greater than average returns historically, then an assumption is made that a portfolio based on these characteristics will outperform in the future. The last count I have, which seems to change daily, is that there are more than 300 different factors that people claim offer better than average returns. Of course finding something which worked in the past is meaningless unless the future is identical to the past.
Trying to identify factors that provide superior returns has had its rewards. But not in the way you might think. I want to share a little story about a young man who early in his career thought he was pretty darn smart. In fact, he was so full of himself that he knew with a little extra effort he could find a way to build portfolios that would perform better than everyone else’s.
This young man, with a brand new CFA (Chartered Financial Analyst) Charter hanging on his wall, a new computer, and a database full of information on thousands of individual public companies, plus a big head, began a study of the 500 companies that were currently held in the S&P 500 index. He ranked all 500 companies based on S&P quality ratings, price to book value, price to cash flow, price to earnings, dividend yield and a few others factors that he believed were important. To build a portfolio, he divided the 500 companies into five equal weighted portfolios of 100 each. Then he compared the returns of each portfolio to the returns of the entire market Low and behold, if he had purchased the 100 companies with the highest S&P Quality rating at the beginning of the year, and rebalanced at the end of the year, selling those shares whose S&P Quality rating dropped and replacing them with the highest over the past five years, he would have outperformed the S&P 500 by over 3% a year. Not only that, but he would have done it with less risk as measured by a beta of 0.90 over the same five years.
Excited, the young CFA wanted to share this with as many people as he could knowing full well that they would be just as excited about making extra returns as he was. Of course it was a good thing he did not do that until some real-time testing could be done. Since his own portfolio was meager, buying 100 stocks was beyond his means, so he just did it on paper, thinking that if it worked over the next twelve months surely a big investor would come along and reward him for his expertise.
A year later, the young CFA was quite embarrassed at the results. This real-time testing without using real money taught him a pretty good lesson. On review, the young man recognized one problem after another. Let’s take the time to look at a few of these.
- Every year the companies included in the S&P 500 change. There may not be a large number of changes, but changes there are. The original 500 companies used in his study were not the same as the 500 used to build his portfolio. In other words, he was comparing apples to oranges.
- The original results may have had nothing to do with quality. It may have been that those companies with a high quality rating also increased cash flow, or dividends, or the market simply wanted to own quality during the five years for any given reason.
- The original study did not include any extra cost. He did not account for the cost of commissions, fees, or the actual price paid for each company bought or sold during the day instead of just using a closing price. These costs were so great that any outperformance on paper was erased.
- In the real world, five years isn’t even a full economic cycle. Would the performance still be good over a lifetime, and not just the last five years? Would it have performed just as well over a ten year period, or over a five year period twenty years earlier? The recent five years is just too short of a time period to have real meaning.
- If the excess returns were real, and all he needed was S&P’s Quality rating, anyone could find the same quality rating, causing others to piggyback on his research. Given how easy it would be to do that, other investors could easily wipe out any extra returns by driving up the prices of the highest quality companies.
Most of the products created by investment companies that market to you under the heading of smart beta are based on a single factor. This is dangerous for individual investors. The only guarantee is that the future will be different than the past. It may rhyme, but it will not be the same. Trusting your money to a single factor that worked in the past has a far greater chance of producing inferior rather than superior returns in the future.
Our young CFA was able to learn the pitfalls of back-testing without causing damage to himself or his clients. Managing a portfolio to meet long or short term goals is far more difficult than applying a little math. So this is a reminder: use your trump card known as common sense when Wall Street comes calling to offer you their latest great idea to make you rich.
Until next time,
Kendall J. Anderson, CFA