Swedroe: Fund Construction Matters

July 17, 2015

“When I hear ‘smart beta,’ it makes me sick.” So said economist and Nobel Prize-winner William Sharpe after he was asked at a conference last year for his thoughts on strategies of this type.

And while much, if not the vast majority, of what Wall Street terms “smart beta” makes me sick as well, one can make the mistake of throwing the proverbial baby out with the bathwater. Unfortunately, that’s what I believe Sharpe and many others are doing.

I’ve previously explained why most of what is called smart beta is really nothing more than a marketing gimmick. It’s simply the result of loading on factors (such as size, value, momentum and profitability/quality) other than the market beta. In other words, most smart-beta products aren’t delivering alpha, just beta on other factors.

However, as I’ve also previously pointed out, there are some weaknesses with pure indexing strategies that can be minimized, if not eliminated. And creating fund construction and implementation rules that do so could be described as smart beta.

‘Smarter’ Beta

One good example of how a fund can demonstrate “smarter” beta is in its choice of fund construction rules. The point is best illustrated through a regression analysis on the four leading small-cap indexes: the Russell 2000, the CRSP 6-10, the S&P 600 and the MSCI Small Cap 1750.

The following table shows results obtained from a four-factor (beta, size, value and momentum) regression for the period January 1994 through February 2015. The t-stats are in parentheses.

January 1994 - February 2015

Index Annual Alpha (%) Beta Size Value Momentum R2 (%) Annualized Return (%)
CRSP 6-10 0.09 1.0 1.0 0.1 0.0 98 11.3
  (0.2) (89.4) (56.1) (5.6) (-0.4)    
MSCI 1750 -0.05 1.0 0.7 0.3 -0.1 97 11.1
  (-0.1) (70.4) (29.8) (10.7) (-5.1)    
Russell 2000 -1.88 1.0 0.9 0.4 -0.2 96 9.1
  (-2.1) (57.8) (31.6) (11.3) (-8.3)    
S&P 600 -0.15 1.0 0.8 0.5 -0.2 92 10.8
  (-0.1) (43.2) (21.9) (9.9) (-5.6)    

We’ll begin our analysis by observing that all the r-squared figures are relatively high, meaning the model is doing a good job of explaining returns. In addition, all of the loading statistics are highly significant.

As you can see, all four indexes had identical exposure to market beta (1.0). During the period examined, the size premium was 2.4 percent, the value premium was 2.3 percent and the momentum premium was 5.4 percent.

The CRSP 6-10 index had the highest exposure to the size factor (which provided a relative boost to returns) but also the lowest exposure to the value factor. The negative impact of its lower exposure to value offset the benefit of its higher exposure to the size premium, and the index basically produced no alpha.

Find your next ETF

Reset All