Indexology^® Blog

Indexing provides many rewards, including a reduction in volatility. Asset owners should demand higher returns to justify the volatility that active management entails. For managers who put their stock selection skills to the test, it is worth understanding the height of the volatility hurdle in managing a portfolio’s risk/return profile.

We can illustrate this by considering the volatility of a sector index, which, like that of any portfolio, is contingent upon the weights, volatilities, and correlations of its constituents. In particular, the lower the correlations, the greater the reduction in volatility between the constituents and the portfolio will be. Exhibit 1 illustrates this for the S&P 500^® and its 11 component sectors. The S&P 500 is 45% less volatile than its constituent stocks, while the average sector index reduces component volatility by 30%. This effect is more pronounced in certain sectors, such as Consumer Discretionary, Consumer Staples, and Health Care, which have relatively low within-sector correlations.

A portfolio manager can own an entire sector or, alternatively, own only a small number of her favorite stocks. Buying individual stocks typically requires assuming more volatility, which implies an expectation of higher returns. But how much higher? Consider: the Utilities sector historically returned 7.8% annually, which implies 0.50 units of return for every unit of risk. The average Utilities stock is more volatile (22.1%) than the sector as a whole (15.6%). To maintain a constant 0.50 return/risk ratio, the average stock would need to return 3.3% more than the sector as a whole. Exhibit 2 applies this logic to the S&P 500 and to each individual sector.

The required incremental return is greatest in Consumer Discretionary, Consumer Staples, and Health Care, all of which have below-average within-sector correlations. At the other extreme lies Real Estate, where within-sector correlations are quite high.

How likely is it that the required returns from Exhibit 2 are actually attainable? Dispersion, or the spread among returns in a sector, indicates how challenging it might be for managers to generate this incremental return. For the Utilities sector, the 3.3% incremental return amounts to 0.21 “dispersion units” (or, roughly speaking, a stock return 0.21 standard deviations above the sector mean).

Exhibit 3 makes this comparison for all sectors. Consumer Staples and Health Care stand out as particularly challenging. In these sectors, fewer stocks will generate the return sufficient to justify a concentrated position.

Stock selection within sectors entails the possibility of higher returns, but the probability of higher volatility. This framework helps understand within which sectors that incremental volatility is most likely to be justified.

Contrary to the myth that active managers tend to fare better than their benchmarks during volatile markets, 68.83% of domestic equity funds lagged the S&P Composite 1500^® during the one-year period ending Dec. 31, 2018, making 2018 the fourth-worst year for active U.S. equity managers since 2001 (see Exhibit 1).

Evidence from the SPIVA U.S. Year-End 2018 Scorecard puts a question mark over the ability of active managers to generate alpha during market turmoil. In 2018, heightened volatility accompanied by below-average dispersion might have handcuffed active managers in terms of stock picking, and the investment outcome in general seemed more random than usual, as indicated by a relatively large standard deviation of return distribution.

Last year was a rollercoaster ride for financial markets (see Exhibit 2). The S&P 500^® (-4.38%) finished 2018 with its first calendar-year loss in a decade, while the S&P MidCap 400^® (-11.08%) and the S&P SmallCap 600^® (-8.48%) posted even larger losses. Despite elevated volatility levels in 2018, monthly dispersion—the difference between winners and losers—of the S&P 500 remained generally below its long-term average since 2009 (see Exhibit 3). The combination of high volatility and low dispersion in 2018 created a challenge for active managers to generate alpha through stock selection.

Outcomes from active investment decisions in 2018’s market conditions seemed more random than usual. The one-year return distribution of all U.S. large-cap funds showed higher standard deviation compared with medium- and long-term distributions (see Exhibit 4).

For the ninth consecutive year, the majority (64.49%) of large-cap funds underperformed the S&P 500. Similarly, small-cap equity managers found it more challenging to navigate 2018’s market environment compared with 2017’s range-bound market movements; 68.45% of all small-cap funds lagged the S&P SmallCap 600 over the one-year horizon. Mid-cap mutual funds fared better; for the second consecutive year, the majority (54.36%) beat the S&P MidCap 400. Over the fifteen-year investment horizon, however, 80% or more of active managers across all categories underperformed their respective benchmarks.

When do sectors matter, and what can you do about it?  Sometimes the sector composition of an equity portfolio strongly affects its returns.  At other times, single stock effects or overall market effects dominate.

Sector-based products such as ETFs and futures have been around for decades, but recently they have attracted growing interest.  Exhibit 1 illustrates the increase in open interest and volumes in products linked to S&P DJI’s U.S. sector and industry indices since 2013.  Both series show a more-than-doubling of investor usage in the past six years.

Exhibit 1: Growing Usage in Products Linked to Sector Indices

This growth might be attributed to a wider trend toward index-based investing in the general market, particularly by financial advisors.  However, the growth in trading volume handily exceeds the growth of assets under management, which suggests an alternative user base to the traditional “buy and hold” mentality of passive investors.  Active investors might be hedging the sector exposures of their single-stock picks, or they might be making direct bets on the relative fortunes of sectors.  In either case, they seem to be doing more of it than they used to do. 

Why now?  The answer is that the strength of sectoral effects in equities has increased.

We discuss this in depth in our recently published paper, Sector Effects in the S&P 500®, which outlines a method to measure the relative importance of sectors in determining the risks and performance of constituents.  The result of this analysis is shown in Exhibit 2.  When the series of Exhibit 2 rises, it tells us that a stock’s sector membership is of growing importance, relative to its market (S&P 500) membership.  When the series declines, sector effects are less important in driving returns.

Exhibit 2: Sector Importance Has Risen Significantly Since 2013

The rising trend of the series in the past six years offers one explanation for the rising usage of sector-based products, which naturally find greater application when sectoral exposures are more dominant in determining outcomes.

The relative importance of sectors has important applications for effective active management in single stocks, as well as offering a perspective on the extent to which “macro” concerns are driving returns.  For a useful in-depth understanding these sectoral trends, have a read of the paper.  Or to simply monitor the ongoing dynamics of Exhibit 2, follow our monthly sector dashboards for updates.

Since the beginning of 2019, the Brazilian stock market has been in bullish territory, generating double-digit gains in January alone (10.59% in local currency and 17.71% in U.S. dollars).[1] Market participants are calling for a strategy to help them take advantage of the current favorable view on Brazilian equities. The S&P/B3 High Beta Index may offer a solution.

Beta is a measure of the risk of a security with respect to the entire market (as defined in the Capital Asset Pricing Model). In other words, it gives an expectation of how a security return will respond to general market movements.

In a rising market, leveraged strategies are frequently used to gain a multiple of the daily return of a benchmark. Leverage is obtained traditionally via derivatives with their respective expenses, fees, gains, and losses. When compounding daily returns, the result may deviate from the original strategy. Moreover, there are market participants with leverage constraints.

The S&P High Beta Indices are designed to serve as a benchmark for equity strategies that aim to achieve a multiple of index returns without leverage. The indices usually select the securities that exhibit the highest sensitivity to the underlying broad-based benchmark, as measured by beta. Securities are weighted by their betas, with the most sensitive stocks receiving the highest weights in the index.

Therefore, the S&P High Beta Indices allow market participants to initiate a bullish strategy in the short term.

The S&P/B3 High Beta Index is designed to measure the performance of the 25% of Brazilian stocks that are most sensitive to changes in broad market returns as represented by the S&P Brazil BMI. Sensitivity to market movements is the beta of each individual stock over the past 12 months in Brazilian reals.

To review how often the strategy follows the direction of the benchmark, we observed the behavior of the S&P/B3 High Beta Index when the S&P Brazil BMI had positive returns (an up market) and when the S&P Brazil BMI had negative returns (a down market). Results varied when using daily returns or monthly returns. In daily returns, we can see that the S&P/B3 High Beta Index moved in the same direction as the S&P Brazil BMI 85.07% of the time in up markets and 84.66% of the time in down markets. On a monthly basis, the results were different, with the index moving the same direction as the market 81.02% of the time during positive months and 91.58% of the time in down months (see Exhibit 2).

The outperformance rate during the up periods was 53.28%, generating roughly a 1.3% average monthly excess return, while the negative excess return during down periods was -2.56%, outperforming the market just 27% of the time (see Exhibit 3).

The resulting beta of the S&P/B3 High Beta Index versus its benchmark is also aligned with the strategy. Exhibit 4 shows the 36-month rolling beta from Aug. 31, 2002, to Dec. 31, 2018. In 63% of the months, the rolling beta was greater than 1.2.

The results show that the S&P/B3 High Beta Index has provided a multiple of the S&P Brazil BMI return in up and down markets. Because of that, the index may serve as a solution for participants with leverage constraints.

The results also indicate that the use of this strategy is highly tactical. Exhibit 4 demonstrates that the index is not a basis for a buy-and-hold strategy. As geometric compounding kicks in, over a long-term investment horizon, the index underperformed the broad market over the period studied (see Exhibit 5).

[1]   Source: S&P Dow Jones Indices LLC. Data based on the S&P Brazil BMI (Local Currency) (PR). The Brazilian stock market started to show an upward trend in the 1990s until it peaked in May 2008. The S&P Brazil BMI increased to 844.90 from 95.46 a decade earlier. After this, a period of high volatility lasted almost 10 years. Even though the market reached that peak again on Jan. 22, 2018 (at 845.74), it was viewed with caution, as 2018 was an election year in Brazil.

February saw commodities continue their impressive start to 2019. The S&P GSCI was up 3.8% in February and up 13.1% YTD, while the Dow Jones Commodity Index (DJCI) was up 1.9% in February and up 7.4% YTD. Solid performance in petroleum prices continued to support both the S&P GSCI and DJCI, while lagging grain prices detracted marginally from overall market performance. One notable feature of the commodities markets so far this year has been the outperformance of the more industrial commodities (namely energy and industrial metals), compared to the performance of precious metals and particularly the lagging agriculture and livestock commodities. When considered in combination with the strong performance of other asset classes, such as U.S. and emerging market equities, it is likely that much of the strength in commodities markets has been driven by a general improvement in investor confidence and an associated fall in the perceived likelihood of a global economic slowdown, as opposed to any specific commodities supply and demand drivers.

The early-2019 surge in oil prices has reflected concerns regarding a supply shortfall, on the back of sharply lower production in a number of key OPEC countries, including the perilous demise of Venezuela, but there are nascent signs that growth in demand will be weaker this year, which could elevate some of the pressure on supply. The S&P GSCI Petroleum ended the month up 7.7% and 23.5% YTD. To date, Saudi Arabia has shouldered the bulk of the OPEC production cut burden, and this was the focus of the cocktail party circuit during International Petroleum Week in London at the tail end of the month. Other topics of debate included the uncertain economic outlook tied to U.S. trade policy, geopolitical risk surrounding Venezuela and Iran, the implications of the 2020 IMO mandate forcing shippers to cleaner burning fuels, the risks associated with global demand, and last but not least, the U.S. shale supply juggernaut and growing U.S. oil exports.

Renewed optimism regarding the likelihood of a trade deal between the U.S. and China supported industrial metals in February. The S&P GSCI Industrial Metals rose 3.1% in February, while the DJCI Industrial Metals was up 4.0%. Copper was the star performer (up 5.9%), while nickel continued to surge higher (up 4.6% in February and up 22.1% YTD). Refined metals have been flowing in sizable volumes to China, reducing availability in the rest of the world and further pressuring global metal exchange stocks, which are already low—a function of relatively weak mine supply growth and some changes to LME warehouse rules.

The S&P GSCI Gold struggled to maintain its recent strength into month end (down 0.5% in February but still up 2.6% YTD). Providing a solid foundation for bullion during the bulk of February was U.S. Fed Chairman Jerome Powell’s reiteration that the central bank would remain “patient” while deciding the future of interest rates. A precious metal requiring little support from central bankers so far in 2019 has been palladium; the S&P GSCI Palladium has surged 26.7% YTD. The auto catalyst metal has climbed on the back of widening supply tightness, while threats of strikes by mineworkers in South Africa has added further support.

Across the agriculture complex, performance was skewed to the downside (S&P GSCI Agriculture down 5.0% for the month and off 2.9% YTD). Wheat had a particularly challenging month, with both the S&P GSCI Wheat and S&P GSCI Kansas Wheat ending the month down more than 11%. Wheat has come under pressure amid concerns that U.S. exports will continue to face stiff competition in global markets particularly from more competitively priced Black Sea wheat suppliers such as Russia.

The S&P GSCI Livestock was up a marginal 0.2% for the month. Lean hogs (down 7.0% for the month and off 13.6% YTD) continued to be a drag on the broader index due to much higher levels of U.S. pork production than expected and ongoing market access restrictions for U.S. pork in key export markets. Should China and the U.S. reach an agreement on trade, the lean hog market may prove to be a major beneficiary.

See more details on how the commodities measured by the S&P GSCI and the DJCI fared here.