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Thermal Coal Companies Removed from the S&P 500® ESG Index in Response to Market Demand

Profitability, Liquidity, and Investability: The Key Drivers of Long-Term Outperformance of S&P SmallCap 600® versus Russell 2000

A Practical Look at How Risk is Shifting in Sectors

Why Reach for Yield When You Can Use a Ladder?

Sectors and Electors

Thermal Coal Companies Removed from the S&P 500® ESG Index in Response to Market Demand

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Mona Naqvi

Global Head of ESG Capital Markets Strategy

S&P Global Sustainable1

The fast-changing nature of the ESG landscape is no stranger to those within it. Competing definitions, variability in scoring methodologies, and a spectrum of individual investor objectives have made fertile ground for divergent approaches. However, among this slew of sustainable investment strategies, common threads have emerged. When the S&P 500 ESG Index was launched in January 2019 as an accessible starting point for ESG investors around this world, it did so by excluding the types of business activities deemed unacceptable by the broadest possible majority of sustainability-minded investors and selecting constituents according to their relative S&P DJI ESG Score performance within index and industry groups. At the time, this meant avoiding companies involved in controversial weapons and tobacco, in addition to other sustainability screens not specifically tied to business involvement.1 Just over 19 months later, the landscape has evolved to a point at which thermal coal companies may now be counted among this lowest common denominator of “unsustainable” investments. Thus, after an industry-wide, public consultation that confirmed this shift in investor perception, the S&P ESG Index Series Methodology was updated to exclude thermal coal in an extraordinary rebalance that took effect on Sept. 21, 2020.2

Rebalance Results

As of the rebalance, 299 constituents made it into the S&P 500 ESG Index, with 78 ineligible companies and 125 deemed eligible but not selected due to relatively poorer S&P DJI ESG score performance compared with their index industry group peers. Exhibit 1 shows how the S&P 500 now translates into the composition of the S&P 500 ESG Index.3

But what’s really changed? Unsurprisingly, the changes were primarily driven by companies removed due to having more than 5% of their revenues coming from thermal coal, as defined by the new exclusion rule.4 However, only 11 of the 17 thermal coal companies within the S&P 500 were dropped from the S&P 500 ESG Index, as the rest were already excluded due to one of the preexisting exclusion and selection criteria. Subsequently, 4 names were added, as these departures made room for new joiners and the methodology must target 75% of the float-adjusted market cap (FMC) within index and industry groups (where companies are ranked by S&P DJI ESG Score).5 A further 10 companies were dropped as they were no longer required to target 75% FMC within their index industry groups—unrelated, specifically, to the removal of thermal coal companies. Eight new names were thus added due to non-thermal coal exclusion-related changes in the S&P 500. Exhibits 2 and 3 outline the largest 10 additions and drops in order of market capitalization.

Impact of Removing Thermal Coal

To properly assess the impact of excluding thermal coal companies, the index objective has to be considered. The S&P 500 ESG Index is designed to reflect a sustainable, broad-based measurement of the U.S. equities market, with similar overall industry group weights as the benchmark S&P 500. As such, changes to the methodology need to be evaluated in the context of its implicit goal of keeping the tracking error low. As part of the consultation, data showing the realized tracking error of the S&P 500 ESG Index versus the S&P 500 between the 2019 and 2020 annual rebalances (1.08%) was thus compared to the hypothetical results that would have occurred had the new 5% thermal coal exclusion rule been in effect (1.11%).8 Based on this analysis, the removal of thermal coal companies does not appear to diminish the index’s ability to meet its objective. This important result, alongside the positive response from market participants generally in favor of the new rule, underpinned S&P DJI’s decision to implement this change. This decision reflects S&P DJI’s ongoing commitment to creating ESG indices to match investor conviction, as the lines surrounding the sustainable investment landscape continue to be drawn.



1 The S&P ESG Index Series Methodology additionally excludes companies that perform poorly on the principles of the UN Global Compact (UNGC), companies involved in controversies deemed material to their ESG performance (according to the SAM Media & Stakeholder Analysis [MSA]), as well as companies that rank among the bottom 25% of S&P DJI ESG Scores, globally. As of Sept. 21, 2020, companies with more than 5% of revenues generated from thermal coal were added to the list of ineligible companies for the index series.

2 The public consultation, which ran from March 23, 2020, to May 29, 2020, outlined several options for the proposal and their potential impacts, which may be found here. As most respondents were generally in favor of excluding companies with more than 5% of revenues generated from thermal coal, the S&P DJI Index Committee announced on June 12, 2020, its decision to implement this new rule via an extraordinary rebalance that would take effect on Sept. 21, 2020. Following this rebalance, the index will return to its normal schedule of annual rebalances, effective after the close of the last business day of April.

3 For more information about the last official annual rebalance in April 2020, please refer to this May 2020 blog announcing the changes. Deeper dive analysis examining the impacts of the S&P 500 ESG as of the April 2020 annual rebalance can also be found in our recently published piece “The S&P 500 ESG Index: Defining the Sustainable Core.”

4 The consultation asked market participants whether the S&P ESG Index Series Methodology should exclude companies with revenues generated from thermal coal, and if so, whether the appropriate revenue threshold should be set at 25%, 10%, or 5%. S&P DJI opted to select the strictest measure based on the consultation results.

5 For more information about the index series methodology, including how it targets 75% FMC within index industry groups, please refer to the S&P ESG Index Series Methodology.

6 Other household names dropped from the index include News Corp and H&R Block. News Corp was eligible but no longer required to target 75% FMC within its index and industry group. H&R Block was dropped due to underlying changes in the S&P 500.

7 Companies added due to underlying changes in the S&P 500 were added either due to changes in the underlying constituents comprising the index industry group, or due to existing constituents losing market capitalization, essentially requiring additional companies be added when targeting 75% FMC.

8 Data from April 30, 2019 to April 30, 2020.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Profitability, Liquidity, and Investability: The Key Drivers of Long-Term Outperformance of S&P SmallCap 600® versus Russell 2000

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Wenli Bill Hao

Director, Factors and Dividends Indices, Product Management and Development

S&P Dow Jones Indices

The S&P 600TM has outperformed the Russell 2000 since its launch in 1994. From Dec. 31, 1994, to Aug. 30, 2020, the S&P SmallCap 600 had an annualized return of 11.77% (with an annualized volatility of 18.96%) versus the Russell 2000’s annualized return of 10.49% (with an annualized volatility of 19.70%).

The historical performance divergence is due to differences in index construction, as shown in Exhibit 1. Notably, the inclusion criteria of positive earnings, liquidity, and public float result in the constituents of the S&P SmallCap 6001 being more profitable, more liquid, and more investable than those of the Russell 2000. In this blog, we explore the validity of profitability, liquidity, and investability screening in index construction.

To attest the overall impacts of profitability, liquidity, and investability, we compare the returns of two hypothetical portfolios constructed by dividing the Russell 2000 (R2000)2 universe:

Group 1: Consists of securities that satisfy criteria of profitability, liquidity, and investability as defined for the S&P SmallCap 600.

Group 2: Consists of securities that are not included in Group 1.

For each group, we form equal-weighted and cap-weighted portfolios. Similarly, we also weight the universe equally and by market cap. To show the robustness of our findings, we present the results of the equal-weighted and cap-weighted portfolios. The portfolios are rebalanced monthly.

Equal-Weight Results

During the period studied, about 700 companies in the Russell 2000 universe would have been in Group 1 and about 1,300 companies in Group 2. Exhibit 2 shows that Group 1 outperformed both Group 2 and the Russell 2000 universe in terms of total return and risk-adjusted return. Such findings indicate that more profitable, liquid, and investable companies tend to outperform their peers in the Russell 2000 universe.

Another important finding is that S&P SmallCap 600 Equal Weighted Index had similar returns to Group1 and naturally outperformed the equal-weighted Russell 2000 universe. The S&P SmallCap 600 Equal Weighted Index achieved its outperformance by using the inclusion criteria of profitability, liquidity, and investability and using only 600 stocks versus 2,000 stocks in the Russell 2000.

Cap-Weighted Results

Exhibit 3 shows that the cap-weighted portfolio of profitable, liquid, and investable small-cap securities outperformed the portfolio of other members in the Russell 2000 universe and the underlying Russell 2000 benchmark. Once again, the S&P SmallCap 600 had practically the same returns as Group 1 in the Russell 2000 universe and outperformed the Russell 2000.

All else equal, the outperformance in the small-cap space came from companies that are profitable, liquid, and investable (Group 1), as captured by the S&P SmallCap 600. Composed of a fraction of stocks in the small-cap universe, the S&P SmallCap 600 could be easier to implement. In sum, the S&P SmallCap 600 is the model benchmark in the small-cap space.


1 For more detailed index methodology information, please refer to Brzenk, P., W. Hao, and A. Soe. “A Tale of Two Small-Cap Benchmarks: 10 Years Later.” S&P Dow Jones Indices. 2019.

2 We use the holdings of iShares Russell 2000 ETF (ticker: IWM) as a proxy for the Russell 2000 universe. Our testing period ran from December 2002 to December 2018 due to the quality of IWM holding data improving after December 2002.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

A Practical Look at How Risk is Shifting in Sectors

How can the relationship between sectors and factors help investors identify market regime changes and inform allocations? S&P DJI’s Anu Ganti and Hamish Preston take a closer look at market trends through the lens of S&P Composite 1500® data.



Learn more:

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Why Reach for Yield When You Can Use a Ladder?

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Jason Giordano

Director, Fixed Income, Product Management

S&P Dow Jones Indices

The current low interest rate environment is forcing many investors to reassess their risk tolerances. Typically, fixed income investors have three main options when trying to “reach” for yield: 1. Move down in credit quality (i.e., take on more credit risk); 2. Increase duration (i.e., take on more interest rate risk); or 3. Move to alternative assets (i.e., those that can potentially incur other illiquidity and lockup provisions). Of course, all of these options pose the same question: Is the incremental yield worth the additional risk?

Staying within the U.S. fixed income asset class, Exhibit 1 shows the broad credit characteristics most investors are currently facing. As expected, a move from BBB investment-grade corporate bonds to BB “junk” bonds produces a 174 bps pick up in yield; however, investors must be willing to tolerate a significant deterioration in credit quality, as well as an exponential increase in default risk. Interestingly, the S&P National AMT-Free Municipal Bond Index has a taxable equivalent yield (TEY) that is 17 bps higher than the yield-to-worst of the S&P U.S. Investment Grade Corporate Bond A Index, offers higher credit quality (AA- versus A), and has a historical default probability of nearly 0%.

For investors uncomfortable with taking on additional credit risk or interest rate risk, a laddered approach presents an alternative. Bond laddering is a mechanism widely used by the investment community to mitigate the potential risks related to buying individual bonds. A ladder helps smooth out the effect of fluctuations in interest rates because there are bonds maturing every year based on the number of rungs in the ladder. When a bond matures, an investor could reinvest that principal in a new longer-term bond at the end of a ladder. Investors may then benefit from a new, higher interest rate, while maintaining the length of the ladder. As shown in Exhibit 2, instead of buying one bond with a six-year maturity, investors can allocate to six different bonds, whereby each bond matures at a different year throughout the six-year horizon.

Investors determine how many rungs their municipal bond ladder should have based on their time horizon. If the goal is to keep the bond ladder in place over time, then as the earliest bond matures, the ladder strategy replaces it with a bond of equal principal at the longer end of the maturity ladder (see Exhibit 3).

The strategy illustrated in Exhibits 2 and 3 allows for construction of a diversified portfolio of bonds from different issuers at each rung of the ladder. Taking this concept a step further, investors have the option of using ETFs that have been specifically designed to incorporate this same structure.

S&P Dow Jones Indices produces a series of indices that seek to track the municipal bond market: the S&P AMT-Free Municipal Series Indices (see Exhibit 4). These indices were designed to reflect the characteristics of a diversified group of bonds that are all high quality, fixed rate, non-callable, and tax exempt. Additionally, each index in the series is composed exclusively of municipal bonds that mature in the stated year, allowing for targeted return of principal and potential reinvestment.

As shown, bond ladders offer a simplified approach when navigating uncertain interest rate environments, while also providing relatively predictable levels of income. For more details and examples of how implementing a laddering strategy using indices can offer additional benefits, please be sure to read the recently updated education piece: Bond Laddering with the S&P AMT-Free Municipal Series Indices.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Sectors and Electors

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Craig Lazzara

Former Managing Director, Index Investment Strategy

S&P Dow Jones Indices

Markets expect elevated volatility surrounding the U.S. Presidential election, now just six weeks away. The VIX futures curve currently peaks in November, but as long ago as April a close observer could detect expectations of electoral volatility. Increased volatility may create an unusual opportunity for sector allocators.

To understand why, we need to remember that volatility is directly connected to dispersion, which measures the spread among the returns of an index’s components. When volatility goes up, dispersion tends to rise as well, as the gap between winners and losers widens; we saw a spectacular example of this in the first quarter of 2020. The greater the spread, the greater the opportunity to add (or subtract) value.

Dispersion can be measured at various levels of granularity—for example among stocks or sectors in the S&P 500®, as illustrated in Exhibit 1. Obviously, the spread among the returns of 500 stocks will be greater than the spread among the returns of 11 sectors. (The larger spread is partially offset by the superior capacity of sector-based funds.)

The total dispersion of the S&P 500 (at the stock level) can be decomposed into the average dispersion within each sector and the dispersion across sectors. The nature of the relationship will be familiar to anyone who remembers high school geometry: the square of total dispersion is approximately equal to the sum of the squares of within-sector and cross-sector dispersion.

Over time, cross-sector dispersion has accounted for approximately 22% of the market’s total dispersion. But the overall average masks substantial calendar variation. As Exhibit 2 shows, the importance of sector dispersion peaks in November and is relatively low in March.

And as it turns out, some Novembers are more significant than others. Specifically, in 71% of the Novembers when U.S. Presidential elections took place, the importance of cross-sector dispersion in the S&P 500 was greater than average, as shown in Exhibit 3. In off-year elections (with only Congressional and Senate seats at stake, but not the White House), sectoral importance also rises, although not to the level of Novembers with a Presidential contest.

Dispersion, it’s important to remember, is a double-edged sword. Higher dispersion raises the stakes for active managers, in both directions: if dispersion is high, correct stock or sector picks will pay off more, and incorrect picks will underperform by more. History tells us that the contribution of sectors to total dispersion is likely to rise in the next six weeks, which means that the importance of skillful sector picks will increase. For investors with a genuine ability to rotate across sectors tactically, November could be a month of unusual opportunity.

The posts on this blog are opinions, not advice. Please read our Disclaimers.