Indexology^® Blog

The S&P 500 Low Volatility Index^® made a valiant comeback in late 2018 after trailing for most of the year.  The strategy index finished the year well by just staying in positive territory at a 0.27% gain, when the broader S&P 500 declined 4%.  It was also the best performing factor index among those based on the S&P 500.  To date in 2019, it is predictably trailing the broader benchmark, up 9.2% versus a gain of 10.1% for the S&P 500.

Since the last rebalance for the S&P 500 Low Volatility Index, volatility continued to increase universally across all sectors of the S&P 500.  Among the sectors that increased the most in volatility was Information Technology, up five percentage points, while Utilities’ volatility increased the least.

It is therefore not surprising that the low volatility index increased its weight in Utilities in the latest allocation shuffle; the sector now composes a quarter of the index.  The other significant shift was Health Care, which gave back what it gained in allocation in the previous rebalance.  Unexpectedly, Information Technology’s weight in the low volatility index remained more or less unchanged. This likely means that volatility levels of stocks within the sector were widely dispersed, with pockets of relative stability.

A headline from yesterday was very intriguing: “Why investors crave a return to the art of stock-picking.”  Copious data demonstrate the peril of placing hope in active management.  The article argues that since we seem to be in a trend that favors value, it is a good time for managers to pick stocks based on fundamental value metrics.

The point that value has recently been beating growth has some merit.  The chart below shows the performance cycles for S&P 500 Growth versus S&P 500 Value since 1995.  There has been a shift in course since October 2018, with the growth index declining 8% versus just 4% for the value index.

Value, like many other factors, cycles in and out of favor. When it is in vogue, value managers might have an easier time beating the broad market—a value manager might well look good against the S&P 500 when value is beating growth.  But that doesn’t necessarily mean that he is adding value as an active value manager.

It is important, in other words, not to conflate the performance advantage of value over growth with the process of stock selection within a value universe.  To do otherwise is to confuse style with selection.

The “indicization” of many investment strategies has allowed for cheap access to previously-unavailable factor strategies. The availability of factor indices “…makes the active manager’s life harder.  In former days, he could expect to be paid both for providing access to factor exposures as well as for stock selection; today, he’s increasingly limited to stock selection as factor exposure is indicized.”

Value might be back in favor, but that does not imply that beating a value index by stock selection is likely. S&P Dow Jones Indices’ SPIVA report also covers style fund managers— whose results are consistent with those of broad market fund managers.  Most style managers underperform their respective benchmarks most of the time.

Recently, a number of reports highlighted a surge in popularity for actively managed U.S. equity funds in 2019.  The main explanation for this trend appears to be the volatility observed in the final few months of 2018: market participants seem to believe active managers are better able to navigate more volatile markets.  However, the data belies this belief: most active managers underperform regardless of market direction.

One possible explanation for the underperformance of active managers involves their typical bias towards high beta, more volatile stocks. Given many funds target 100% participation in market gains, but they may maintain a non-zero allocation to cash equivalents (in order to meet operational needs, for example), many active managers may be obliged to bias their portfolios towards stocks with a higher-than-average sensitivity to market movements.  However, given their higher betas, these stocks generally fall by more than the market during more turbulent times.  In contrast, we expect less volatile stocks (such as constituents of low volatility indices) to be better insulated against market downturns.

Exhibit 2 shows the possible impact of active managers’ apparent preferences for more volatile stocks:  while most U.S. large-, mid-, and small-cap funds lagged their respective benchmarks in most calendar years, the extent of the underperformance was higher in years when low volatility indices fared relatively well.   For example, on average, 58.13% (67.97%) of U.S. large-cap equity funds lagged the S&P 500 in the five years when the U.S. equity benchmark posted the best (worst) annual excess returns.   Similar results can be seen for mid- and small-cap managers, based on the relative performance of the S&P MidCap 400 and S&P SmallCap 600 to their respective low volatility indices.

So how did low volatility indices perform in 2018?   The S&P 500 Low Volatility, S&P 400 Low Volatility, and S&P 600 Low Volatility indices all beat their cap-weighted counterparts last year.  And the annual excess returns for each of the low volatility indices ranked 6^th, 3^rd and 9^th, respectively, across all years since 2001.

As a result, we will have to wait for our year-end 2018 U.S. SPIVA numbers to see how active managers fared against their benchmarks in 2018.  However, historical evidence suggests the relative performance of low volatility indices – among other factors – may be a sign that active managers struggled to beat their benchmarks amid the recent market jitters.

Active managers were welcomed by a disheartening headline this morning. “The 2018 Comeback That Wasn’t for Stock Pickers” highlights that “just 38% of actively managed U.S. stock funds tracked by Morningstar outperformed their counterparts at passively managed funds last year.”  This should hardly have been considered shocking.  Both long-term and more recent data (notably including our SPIVA reports) document the consistent underperformance of active managers. However, active managers’ relative performance does fluctuate, as evident from the chart below, and some years are clearly tougher than others.

Based on SPIVA data from 2001 to 2017, we’re able to identify some environments in which active managers seemed to deliver relatively better results. Among them are years in which dispersion is high, when low volatility stocks underperform, and when megacaps underperform.

Significantly, none of these conditions occurred in 2018.  Dispersion (despite rising in the latter part of the year) was below long term average, the S&P 500 Low Volatility Index was the best performing strategy index, and megacaps narrowly outperformed smaller stocks.

Most active managers underperform most of the time.  Nothing in 2018’s data suggests that the year should have been an exception to that general rule.

The S&P Style Indices and S&P Pure Style Indices take distinct approaches in differentiating between value and growth factors. In past blogs,[1] we examined how differences in index construction can affect the performance of the indices in both series over a long-term investment horizon. In this blog, we examine how the suite of pure style and style Indices behave in various market and style cycles.

When looking at the correlation of value and growth pairs for both sets of indices (see Exhibit 1), we see that the pure style indices exhibited lower correlations between value and growth than their traditional style counterparts. In other words, there was a higher correlation spread between pure style indices than the traditional style indices.   The relative performance of value and growth indices moves in cycles over time, thus market participants could potentially make tactical adjustments to take advantage of short-term deviations in relative value. Exhibit 2 illustrates the style return spread (value minus growth) for the large-cap, mid-cap, and small-cap style and pure style indices.

During periods when one style was favored over the other, the return spreads of the pure style indices were markedly wider than the style indices across all cap sizes. Also, the pure style indices typically had higher performance in the direction of the favored style (see Exhibit 3). Therefore, the greater discriminatory power of the pure style indices may allow for more effective style rotation strategies and hedging tools.

Over the study period, when value was in favor, pure value outperformed value the majority of the time across all size segments. However, when growth style was in favor, we find that results were mixed. In large caps, growth outperformed pure growth slightly more often (52% to 48%), while the average excess return of pure growth versus growth was positive (0.16). In mid caps, pure growth did better than growth more often, while growth did slightly better than pure growth in small caps.

The asymmetric performance of the pure style indices indicates that they may have more sensitivity to market movements than the style indices. We next compute the betas of pure style and style to their respective benchmarks (see Exhibit 4).

On average, the traditional style indices each had betas close to one, meaning the style indices generally moved in the same direction and magnitude as the respective benchmark. This points to the standard style indices potentially being a suitable choice for strategic long-term equity market exposure, with a slight tilt to the desired style.

The pure style indices all had average betas higher than one. Therefore, in an up market, pure style indices could be expected to do better than the style indices. Conversely, in down markets, pure style indices may underperform their style counterparts.

Market participants may look to use growth and value together in a portfolio, tilting to one side based on their views. In an upcoming post, we will analyze the effect of combining value and growth at varying weights in hypothetical portfolios.

[1] https://www.indexologyblog.com/2019/01/15/pure-style-indices-a-finer-tool-with-higher-style-focus/

https://www.indexologyblog.com/2019/01/28/sp-pure-style-indices-versus-sp-style-indices-the-impact-of-security-selection-and-weighting-on-excess-returns/

https://www.indexologyblog.com/2019/01/30/reviewing-sp-pure-style-indices-from-a-sector-perspective/