Source: etfstream.com

If you follow my Instagram page, you may notice that from time to time I post about smart beta ETFs and mutual funds. These are funds or ETFs that follow strict investing rules for the stocks that they include in their fund. They then have rules about how often they re-evaluate the portfolios and when they are rebalanced.

I like the general concept of this because I think it takes the human element out of investing which I think is the cause of a lot of subpar returns when it comes to investing. Research has consistently show that most managers just don’t beat the index over the long run. It’s a bit like playing chess against a super computer, the human is racking their brain as to how to win and how to beat their opponent (in this case the index) while the computer just hums along, emotionless. The human eventually tires out or admits defeat. Hence why computers now can beat all the chess champions.

With investing it may be even harder. I see a lot if posts now saying if you had bought 1000 shares of Amazon 25 years ago, you’d be a millionaire today, but hindsight is 20-20. Who had any idea at the time or even up to a few years ago that Amazon would pivot and re-pivot the company to become an online behemoth that would take on Wal-Mart?

The market shifts as well, there are a number of factors that produce this, consumer tastes change, demographics change, governments change, which can change the behavior of a country’s citizens or the market. It’s hard to consistently be right and spot all the trends before you find yourself behind the ball and play catch up.

The Potential Flaw with Smart Betas

Let’s assume in this case that the S&P 500 is our benchmark, or what we measure our performance against. Smart Beta funds usually start out as follows: there are a number of academic studies that show that certain strategies or characteristics of stocks beat the market over the long run.

The makers of the smart beta ETFs or funds then go out and put these into practice. Of course with the academic observation backing them up, they can extrapolate past returns that make it look like the strategy and the fund are going to be real winners.

At the heart of it though, you are testing one rules based system versus another and betting that one system will beat the other over the long term moving forward. There are a number of famous examples from Wall St. lore of strategies that were done based on looking at past data and shown to beat the index, only to be traded away once people knew about them because the masses all piled into the same strategy and brought the long term returns above the index either down to zero or even negative.

One of the most famous examples is the Dogs of the Dow. This was a strategy popularized by Michael O’Higgins which takes the 10 stocks in the Dow with the highest dividend yield and invests in those for the next year. There is also a strategy derived from this called the Small Dogs of the Dow which takes those 10 stocks and then picks the 5 with the lowest price (I could not figure out if this meant dollars per share price or price to earnings) and invests equally in those.Source: dogsofthedow.com

Although these two strategies were wildly successful in the past, the small dogs strategy returned 20.9% from 1973 to 1996, they are less impressive now, beating the Dow and S&P by a percentage point or two since the mid 90’s when these strategies became well known.

What This Means for Smart Betas

There was a great article in Seeking Alpha that covered this topic by a former portfolio manager and he pointed out that many smart beta funds and ETFs suffer from what is called “publication effect” where after the strategy is publicized, it then cannot live up to the returns that it promises in the past because the strategy is arbitraged away by the wider market participants who already are aware of it. Maybe that run up was all the “smart money” moving into the strategy helped push up the performance. Once the “dumb money” arrives through investments into the ETF from retail investors, the initial stakeholders in the strategy sell down their share, contributing to lower prices and lackluster performance.

In fact the fund that I looked at today, the Double Line Shiller Enhanced CAPE find, just seems like a variation of the Dogs of the Dow: it takes the 4 lowest priced sectors of the S&P 500 based on their CAPE (the cyclically adjusted price to earnings ratio, or price to average earnings over the past 10 years). Although this strategy has worked this year and in past years, there is no guarantee it will be home run it once was.

With so many smart beta funds as well, you start to have to wonder about whether liquidity would also play a factor if you needed to get rid of these ETFs, some of the ones I looked at on ETF Database had $150 million in assets, which is quite small.

Conclusion

With over 900 smart beta ETFs and funds it remains to be seen if this democratization of hedge fund like strategies will pay off for the little guy but my hunch is that the next great investor will likely not be implementing his great strategy through smart beta ETFs.

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