Indexology^® Blog

The last few days have been turbulent for financial markets as coronavirus contagion fears took hold.  Global equities fell; the S&P 500®’s 6.6% price return plunge since the end of last week wiped off its year-to-date gains; recent U.S. sector and industry declines mean that nearly all S&P Composite 1500® industries are down month-to-date; and safe havens rallied – the 10-year U.S. Treasury yield hit an all-time low on Tuesday.  Unsurprisingly, perhaps, VIX® spiked earlier this week, closing above 25 for the first time in over a year on Monday.

Amid the recent turbulence, people may be tempted to turn their back on equities in favor of so-called safe havens.  But while this strategy may help to mitigate losses in the short-term, it is worth remembering that rotating out of equities has risks, too: the difficulty in timing the market means there is a danger of missing out on upside participation.  This is especially relevant given the current dispersion-correlation environment suggests it is unlikely that we’re on the cusp of a sustained bear market.

Exhibit 2 shows the average 1-month, 1-quarter, 6-month, and 1-year S&P 500 price return following various daily price returns for the U.S. large-cap equity benchmark, based on data over the last 50 years.  The daily price returns (x-axis) were chosen such that 5% of daily moves fell into each “bucket”.  Quite clearly, the S&P 500 typically rose, with stronger price returns usually following larger market declines.  For example, the subsequent returns for the leftmost bucket ranked as the first, second, second, and third highest across 1-month, 1-quarter, 6-month, and 1-year horizons, respectively.

Given the inherent difficulty in correctly anticipating market movements – for example, not many people predicted the S&P 500’s record-setting start to 2019 following the turbulent Q4 2018 – using sectors to express views may provide a useful way to maintain asset allocations while dialing risk up or down within equities: sector rotation can be just as powerful in allowing market participants to express views.

And for those considering turning to active management under the belief that active managers are better able to navigate periods of market volatility, our Risk-Adjusted SPIVA Scorecard offers pause for thought.  Most U.S. equity active managers underperformed their index benchmarks on a risk-adjusted basis over 5-, 10-, and 15-year horizons.  In other words, there is little evidence to suggest that active managers are better at managing risks than their index benchmarks.

In conclusion, even though we will have to wait and see how the market works through coronavirus fears, market participants may wish to consider staying the course by maintaining exposure to equities via an indexed-based approach.

The four most dangerous words in investing are “This time it’s different.”  –  Sir John Templeton

As investors ponder the ultimate extent of the coronavirus epidemic, this week’s equity market declines are of natural concern to every asset owner.  The obvious question, after near-record point drops in major indices yesterday and today, is how much worse the damage might get.

To relieve your suspense immediately, I confess that I don’t know.  Furthermore I don’t know anyone who does know, and I am cynical enough to suggest that anyone who claims to know should be presumed to have a tenuous (and possibly mendacious) grasp of reality.  It’s not just the compliance department that keeps us from giving investment advice.

What we can do, however, is to offer some insights from our study of index dynamics.  In 2016, we introduced the dispersion-correlation map to provide perspective on both good and bad markets, as shown in Exhibit 1.

Exhibit 1.  Dispersion-Correlation Map for S&P 500

Each point in the exhibit represents the average dispersion and correlation for the S&P 500 in the indicated calendar year; the numbers in parentheses are the year’s total return.   The exhibit shows that truly bad markets —  the deflation of the technology bubble, or the global financial crisis — have only occurred in the presence of very high dispersion.  The converse is not true — some high dispersion years have seen strong positive returns.  But it’s fair to observe, based on data back to 1991, that high dispersion seems to be a necessary though not sufficient condition for a bear market.

Comparing the month ended February 24th with these historical data suggests that we are not on the verge of a prolonged market decline.  This conclusion is reinforced when we look at monthly data for two notably bad years.

Exhibit 2.  Dispersion and Correlation by Month, 2001 and 2008

The data in Exhibit 2 show dispersion and correlation for individual months, as opposed to the annual averages of Exhibit 1.  It’s  clear that current dispersion levels are far below those prevailing in 2001 or 2008.  This can change, of course — in 21 more days we’ll have a completely new set of observations.  And it’s certainly possible that the pattern we’ve observed for the past 30 years can admit of an exception.  But unless such an exception occurs, or unless dispersion increases dramatically from its current level, it seems unlikely that we’re on the cusp of a sustained bear market.

In partnership with the ASX, we recently introduced the S&P/ASX All Technology Index, which, for the first time, brings together ASX-listed companies across a range of industries whose businesses are primarily technology focused. In a market heavily concentrated in banks and natural resource companies, the S&P/ASX All Technology Index provides access to a unique, underrepresented segment of the Australian equities market that has also recently been the country’s fastest-growing sector.

In the past five years, the number of S&P/ASX All Technology Index constituents nearly doubled from 24 to 46, while the total market cap of these companies increased more than fivefold from AUD 17 billion to nearly AUD 92 billion.

As illustrated in Exhibit 2, the S&P/ASX All Technology Index substantially outperformed other major Australian equity sectors and the broader Australian equity market over the trailing one-, three-, and five-year periods ending Dec. 31, 2019. Over the past five years, the index recorded an annualized total return of 17.4% compared with the 9.0% return of the S&P/ASX 200.

In order to fully capture technology-driven businesses in Australia, we felt it was important to expand the scope of the index beyond the GICS® Information Technology sector. This allows the index to include other innovative technology-related industries such as health care technology and companies operating online marketplaces that are classified in other GICS sectors. Exhibit 3 illustrates the top 10 members of the index as of Dec. 31, 2019.

To learn more about the S&P/ASX All Technology Index, please see our Talking Points that introduces the new index.

How do the personalities of two dividend index portfolios look when reviewed under the “Factor Lens”? Using the Optimal Asset Management’s Factor Allocator tool, let’s review two strategies – S&P 500 Dividend Aristocrats and the S&P 500 High Dividend Index.

We can identify the average factor exposures of each strategy since January 1995 by viewing their Best Factor Fits (BFF).

The BFF for the S&P 500 Dividend Aristocrats is the following:

…compared to the BFF of the S&P 500 High Dividend Index:

One observation from the above factor comparison is their similar exposure to Low Volatility.  From there, the differences between the strategies become apparent. To begin, only the S&P 500 Dividend Aristocrats has exposure to Quality. Secondly, the S&P 500 High Dividend Index has a larger exposure to Value and Low Momentum.

So, let’s focus on the differences.  As of November 29, 2019, the following is the performance of each of these factors since January 1995.

When comparing to the S&P 500 benchmark, the S&P 500 High Dividend Index’s larger exposure to Low Momentum appears to have hurt its returns and increased its volatility. Also, High Dividend’s larger exposure to Enhanced Value may have helped its returns but increased its volatility. However, the S&P 500 Dividend Aristocrat’s exposure to Quality appears to have enhanced its performance and reduced its volatility.

How did the individual factors perform during different market regimes when compared against the S&P 500 (benchmark) according to Optimal Asset’s Factor Allocator tool?

One observation is the Factor Allocator indicates Quality’s returns were relatively strong during weak market environments while Low Momentum and Value provided relatively poor returns in this same environment. Another observation provided by the Factor Allocator tool is Low Momentum and Value provided elevated volatility in all market regimes while Quality provided some reduced volatility during periods of weak markets.  One could argue based on this data that the S&P 500 High Dividend Index consisted of less defensive factors when compared to S&P 500 Dividend Aristocrats.

Through Feb. 20, 2020, the S&P 500 Low Volatility Index^® is up 5.9% compared to a gain of 4.7% for the S&P 500. Equities roared out of the gate in 2020 but a hiccup in late January allowed Low Vol to catch up and eventually overtake the S&P 500. Those who are familiar with low volatility strategies are not surprised. The strategy’s explicit goal is to muffle the magnitude of movements—in both directions.

By design, Low Vol aims at protection and participation.  A well-designed low volatility index should go down less when the market is down but also go up less when the market is up. Strong markets are the worst environments for low volatility indices, which generally underperform by the largest margin then. But the trajectory of strong markets also play a role in Low Vol’s performance. Choppiness tends to be Low Vol’s best friend. (Relatedly, the S&P 500 High Beta Index usually does well in strong markets but in this choppy environment, the index is up only 2.2% through Feb. 20, 2020.) Strong markets are generally not times for Low Vol to shine but choppiness often allows Low Vol to close the lag (and occasionally even overtake the lead).

Following the market’s strong finish at the end of 2019, it’s not surprising to see that volatility declined across all eleven S&P 500 sectors.

The latest rebalance for the S&P 500 Low Volatility Index is effective after market close Feb. 21, 2020. Industrials had the biggest increase in weight which came largely at the expense of Real Estate.  Consumer Discretionary and Technology experienced the largest reduction in volatility at the sector level but Low Vol only added an extra percent to its Technology holdings while Consumer Discretionary actually experienced a reduction in weight, pointing to higher relative volatility at the stock level.