I supplemented this test with a more robust regression analysis that sought to explain these index’s returns (over Treasuries) using the market risk premium and monthly changes in the 10-year Treasury yield as explanatory variables. This approach controls for fluctuations in the market to present a clearer picture of how changing interest rates affect performance. Exhibit 2 shows the coefficients from these regressions. These indicate how sensitive each index is to the market and changing interest rates and the direction of those relationships. For example, an interest-rate coefficient of negative 1.1 would indicate that a 1% increase in monthly interest-rate changes corresponds to a 1.1% decrease in the index’s return.
.png)
The regression results corroborate the findings above. Both low-volatility indexes have a significant inverse relationship with interest-rate changes, while the high-beta index has a positive relationship with this variable. These interest-rate coefficients become a little smaller (in absolute terms) after adding small size, value, and momentum as additional variables in the regression, but they are still significant.
As a robustness check, I replicated this analysis for the euro-denominated version of the MSCI Europe Minimum Volatility Index, using the euro-area 10-year government benchmark bond yield collected by the European Central Bank in place of the 10-year U.S. Treasury yield. Like its U.S. counterpart, this index had a significant inverse relationship with interest-rate changes. However, this effect was slightly weaker in the eurozone (the interest-rate coefficient was negative 1.13).
Low-Volatility Strategies for a Rising Rate Environment
Mindful of the impact that fluctuating interest rates can have on low-volatility stocks, S&P developed the S&P 500 Low Volatility Rate Response Index, which PowerShares S&P 500 ex-Rate Sensitive Low Volatility ETF (XRLV, listed in the U.S.) tracks. To determine each stock’s interest-rate sensitivity, S&P runs a regression of stock returns against changes in the 10-year Treasury rate during the past five years. It then ranks all stocks in the S&P 500 by their interest-rate sensitivity and excludes the 100 with the smallest positive (or largest negative) interest-rate sensitivity from the eligible universe. This adjustment modestly reduces the index’s style purity. Of the remaining stocks, the 100 with the lowest volatility during the past 12 months qualify for inclusion in the portfolio, and they are weighted by the inverse of their volatility.
While more than 60% of this index’s portfolio overlaps with the standard S&P 500 Low Volatility Index, as of this writing, some of their sector weightings are very different, as Exhibit 3 illustrates. Utilities are the most notable example. The interest-rate sensitivity screen currently blocks all utilities stocks from XRLV’s portfolio, while they make up 23% of SPLV’s.
.png)
Despite the S&P Low Volatility Rate Response Index’s attempt to limit its interest-rate sensitivity, a two-factor regression analysis revealed that it still exhibited significant negative exposure to interest-rate changes. However, it was less sensitive to interest-rate changes than the standard S&P 500 Low Volatility Index (the interest-rate coefficients for the two indexes were negative 1.59 and negative 2.32, respectively). The S&P 500 Low Volatility Rate Response Index isn’t a silver bullet. It was slightly more volatile than its interest-rate-agnostic counterpart. And its five-year lookback period may not be long enough to accurately reflect a stock’s sensitivity to interest rates in different environments. But it should do better in a rising rate environment than SPLV.
Small-cap stocks should also do better in a rising rate environment because they tend to be more sensitive to the business cycle. Therefore, a small-cap low-volatility strategy, like PowerShares S&P SmallCap Low Volatility ETF (XSLV, listed in the U.S.), should also do better than its large-cap counterpart in that climate, although it will probably continue to exhibit greater volatility. Indeed, this fund had much lower negative sensitivity to interest-rate changes from March 1995 through November 2016 (its coefficient on the interest-rate factor was negative 0.41 in the two-factor regression, which was not statistically significant).
While rising interest rates could create a headwind for low-volatility strategies, many of them are still good long-term investments. These strategies have tended to hold up better than the market during downturns and, despite their interest-rate sensitivity, bounce around less than the market. These attractive characteristics should persist, potentially setting up better risk-adjusted performance than the market.
