Another Look At Exposure To Value Factor
We can also see how the increased popularity of low-volatility strategies has changed their very nature by looking at how the loading factors have shifted over time. Using the tool provided by Portfolio Visualizer, we’ll take a look at the results of regression analysis on the largest ETF, USMV.
The first full month since the inception date of this ETF was November 2011. Data is available for the fund through April 2016. We’ll split the period into two equal parts, November 2011 through January 2014; and February 2014 through April 2016. The regressions include the Fama-French factors of beta, size, value and momentum, and the two bond factors of term and default. In the first half of the period, USMV had a loading on the value factor of 0.21. For the second half of the period, the value loading was -0.04. In other words, USMV moved from loading positively on the value factor to now having a slight loading on growth.
Results from the regression analysis confirm what a simple look at the valuation metrics told us. In addition, the regressions show that the fund has statistically significant exposures to the term premium. The loading on the term premium in the first half of the period was 0.29 and in the second half it was 0.25. At the very least, with interest rates at historical lows, investors should be aware of this exposure to term risk.
There’s a cliché in finance that success can sow the seeds of its own destruction. The flow of cash into the low-volatility strategy has changed the very nature of the funds. While they may still be low volatility, they no longer look like value funds. The lower exposure to the value premium means that they now have lower expected returns.
In other words, since there is an ex-ante value premium, what low volatility is predicting at this point in time is not higher returns, just low future volatility. In addition, it doesn’t seem likely that low-volatility strategies will benefit as much in the future as they have in the past from their exposure to term risk.
The bottom line is that the evidence suggests you would be better served by investing in vehicles that screen out the high-volatility (or high-beta), high-risk stocks. In other words, invest directly in size, value and profitability rather than doing so in the indirect way characteristic of defensive strategies.
Larry Swedroe is the director of research for The BAM Alliance, a community of more than 140 independent registered investment advisors throughout the country.