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What Is the Impact of a Company’s Environmental Data on its Weight in an Index?

Combining the Quality Factor With Dividend Yield: A Study of S&P DJI Dividend Strategies

Pure Style Indices: A Finer Tool With Higher Style Focus

Looking at Sectors With a Style Lens

Raising the Bar in Small Caps

What Is the Impact of a Company’s Environmental Data on its Weight in an Index?

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Ryan Christianson

Former Associate Director, APAC Lead, ESG Indices

S&P Dow Jones Indices

One of the key objectives for the recently launched S&P/JPX Carbon Efficient Index is to motivate companies within the baseline index, TOPIX, to increase their level of environmental disclosure. By incorporating a mechanism to adjust constituent weights by their respective environmental data, the S&P/JPX Carbon Efficient Index has been designed to incentivize all companies, regardless of their GICS® industry group, to decrease their carbon emissions relative to their peers and to disclose their environmental impact information.

The S&P/JPX Carbon Efficient Index takes into consideration three different criteria of the S&P Carbon Global Standard[1] when adjusting the constituent weights of the index. The S&P Carbon Global Standard is updated annually at each rebalance reference date using the global universe, the S&P Global LargeMidCap. In Exhibit 1, we present the three different adjustment criteria, and how the carbon weight adjustment may have affected the constituent weights within the S&P/JPX Carbon Efficient Index.

Decile Classification

The decile classification, determined by the S&P Carbon Global Standard, is created by finding the decile thresholds for each of the GICS industry groups based on carbon revenue footprints. Using these thresholds, the eligible constituent universe for the S&P/JPX Carbon Efficient Index is then bucketed into its respective decile classification.

The breakdown of the companies within the S&P/JPX Carbon Efficient Index is relatively evenly distributed among the deciles (see Exhibit 2).

The average percent change of constituent weights shows that there is a significant difference (22% versus -34%) in how the weights are adjusted between companies that have lower carbon-to-revenue footprints compared with those in the bottom three deciles.

Disclosure Status

One of the key goals of the S&P/JPX Carbon Efficient Index is to increase carbon disclosure among the constituents. To achieve this objective, individual companies have been categorized as either “disclosed” or “non-disclosed,” with increased weight allocated to the former. As indicated in Exhibit 1, the difference in weight between disclosed and non-disclosed companies is 10% for each respective decile.

Of the Japanese companies measured by TOPIX, 22.91% have been identified as disclosed companies (see Exhibit 3). When compared to the universe of companies within the S&P Global Ex-Japan LargeMidCap Carbon Efficient Index, which has a 63.55% disclosure rate, it is clear that Japanese companies still have a long way to go for corporate disclosures.

While the disclosure status of a company may not have as big of an impact on the weight adjustment compared to its respective decile, it is clear that it is beneficial for companies to disclose carbon emissions. While the increase in weight may not appear to be significant, the 8.62% decrease in weight as a result of being classified as a non-disclosed company can be quite significant.

Industry Group Impact Factor

When there is a low range of carbon emissions within an industry group, the overall impact on the portfolio of a single company improving their carbon-to-revenue footprint will be low. On the other hand, if a company in an industry group that has a tendency to have a high amount of carbon emissions (such as those from the Energy or Materials sectors) were to improve its carbon-to-revenue footprint, it would potentially make a big impact on the overall portfolio’s carbon-to-revenue footprint.

As a component of the S&P Global Carbon Standard, each GICS industry group is classified as high, mid, or low impact, depending on the range of the carbon-to-revenue footprint, and a larger weight adjustment is made for companies in high impact industry groups (see Exhibit 4).

A high impact classification does not necessarily imply that the industry group is bad for the environment. Because this classification is determined by the range of the carbon-to-revenue footprint within an industry group, it is likely that a high impact industry group is not universally efficient, and thus may have a high opportunity for companies to review their environmental data, which could make it a leader within their respective industry. As the range of carbon-to-revenue footprints within an industry group decreases, it is likely that the companies within the industry group are operating their businesses in the most efficient manner relative to its peers.

The statistics provided in this report are based on constituent weights as of Oct. 31, 2018, and the carbon disclosure information as of the index rebalancing reference date (February 2018).

For the purposes of this report, only constituents that had reported Trucost data at the time of the index rebalancing reference date are included. Since the rebalancing reference date in 2018, Trucost has expanded the amount of coverage companies globally to over 14,000 and has over 99% coverage of TOPIX, as a percentage of total market capitalization.

The TOPIX Index Value and the TOPIX Marks are subject to the proprietary rights owned by the Tokyo Stock Exchange, Inc. and the Tokyo Stock Exchange, Inc. owns all rights and know-how relating to the TOPIX such as calculation, publication and use of the TOPIX Index Value and relating to the TOPIX Marks.

[1] For more details on the S&P Carbon Global Standard, please visit

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

Combining the Quality Factor With Dividend Yield: A Study of S&P DJI Dividend Strategies

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Qing Li

Director, Global Research & Design

S&P Dow Jones Indices

As of Dec. 31, 2018, the passive implementation of dividend strategies measured approximately USD 141 billion based on assets under management (AUM) of dividend-focused ETFs listed in the U.S. This is a staggering amount considering that only 10 years ago the AUM amounted to just over USD 6 billion.[1] The growth in assets, as well as the number of passive dividend-oriented investment products, is a testament to the popularity of dividend investing.

Dividend strategies come with various investment objectives and target different characteristics. For example, some aim to achieve absolute dividend yields, while others may target steady dividend growth rates or combine other fundamentals such as quality or low volatility with yield. The selection and allocation to different dividend strategies can also play impactful roles. No matter what the yield seeker’s focus is, common challenges they face include dividend cuts and elimination. In addition, companies exhibiting high dividend yield may fall in a “dividend trap,” since high dividend yield can be caused by decreasing stock prices rather than the increasing dividends payments. To minimize these risks, many market participants incorporate quality[2] metrics or other filters such as volatility into dividend-focused strategies. These measures aim to ensure that a given dividend strategy is only selecting companies that are capable of maintaining stable dividend distributions and dividend yield, even during periods of market stress.

In this blog, we explore what the impact would be if a quality factor were added to a dividend strategy. For the analysis, we used the S&P 500® Quality High Dividend Index, which is designed to measure the S&P 500 companies that rank among the top 200 in terms of their quality scores and dividend yield.[3] We then compared this strategy against the pure dividend yield, dividend growth, quality, and dividend and low volatility strategies, which are represented by the S&P 500 High Dividend Index, S&P 500 Dividend Aristocrats, S&P 500 Quality Index and S&P 500 Low Volatility High Dividend Index.

Over the long-term investment horizon, all of the dividend-oriented strategies outperformed the S&P 500 on both an absolute return and relative return basis, with the quality and dividend strategy leading the outperformance (see Exhibit 1). Specifically, the quality and dividend strategy outperformed the S&P 500 by 5.42% per year, with an annualized total return of 11.04% versus 5.62% during the past 20 years. The quality and dividend strategy held up relatively well in all market environments, with an average monthly excess return of 0.28%, which was the highest among all the strategies.

Adding quality or volatility filters to a dividend strategy allowed for quicker recovery from the bear market. During the 2008-2009 financial crisis, when all of the yield strategies experienced losses and drawdowns, the data showed that the quality and dividend combination had the smallest drawdown and quickest rebound (see Exhibit 2). The strategy recovered from the financial turmoil within 29 months, versus 53 months for the overall stock market. Meanwhile, the pure dividend yield strategy, as measured by the S&P 500 High Dividend Index, took the longest time to recover.

As displayed in Exhibit 3, the quality and dividend strategy sustained an average dividend yield of 2.92% historically, compared with 1.76% for the S&P 500. While the S&P 500 High Dividend Index historically had the highest dividend yield of 4.47%, it also exhibited the lowest quality traits among all the dividend strategies. As expected, the strategies that incorporated the quality factor demonstrated much stronger quality characteristics.

Dividends are one of the most important drivers in generating investment returns. As we analyzed in this blog, dividend-focused strategies have historically exhibited better long-term outperformance over the market. In addition, when combined with factors such as quality or low volatility, dividend strategies can potentially achieve higher returns and shorten recovery time from bear markets. Specifically, integrating quality and dividend helped generate the highest overall excess return, shortest rebound time, and the highest quality characteristics without sacrificing the yield over the period studied.

[1]   Source:; FactSet.

[2]   Quality definition by S&P Dow Jones Indices:

We define quality as the combination of profitability, earnings and financial robustness, and use return on equity, accruals ratio, and financial leverage ratio to represent these factors.

  • Return on equity (ROE): Indicator of a company’s profitability. ROE is computed as [trailing 12-month earnings per share/book value]
  • Accruals ratio: Indicator of a company’s operating performance. It is computed as [change of net operating asset over past 1-year/average of net operating assets over past two-year period]
  • Financial leverage ratio: Indicator of a company’s capability in meeting its financing obligations. It is computed as [total debt/book value].

[3]   An S&P 500 member company is selected as a constituent if it ranks within the top 200 of the index universe by quality score and ranks within the top 200 of the index universe by indicated annual dividend yield. To reduce sector concentration risk and overall volatility, the stocks are weighted equally and sector weight is constrained at 25%.

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

Pure Style Indices: A Finer Tool With Higher Style Focus

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Aye Soe

Former Managing Director, Global Head of Core and Multi-Asset Product Management

S&P Dow Jones Indices

Style investing as an investment approach has long been utilized by market participants to group securities based on their common characteristics and risk/return drivers. Those common characteristics, in turn, help investors make strategic and tactical asset allocation decisions.

The first-generation S&P U.S. Style Indices serve as effective underlying tools for market participants seeking a passive investment vehicle or benchmarks measuring active style portfolios. Covering broad market segments, the indices group the universe into value and growth categories using style metrics commonly used in the investment community.

Certain securities may exhibit both growth and value characteristics: in this scenario, the company’s market capitalization is distributed between growth and value indices. This makes the indices suitable for those seeking a traditional “buy and hold” index-linked investment implementation with a tilt toward a particular style.

A side effect of this is that there are overlapping securities that fall into both growth and value indices. This mixed basket approach may not appeal to market participants that desire more precise and focused measurement tools.

The S&P Pure Style Indices were created with a stricter definition of style factors, resulting in a clearer differentiation between growth and value. The two approaches to differentiating between value and growth are highlighted in Exhibit 1 using the S&P 500® and the large-cap style (S&P 500 Value and S&P 500 Growth) and pure style indices (S&P 500 Pure Value and S&P 500 Pure Growth) as an example.

 The S&P Pure Style Indices include only securities that exhibit either pure growth or pure value characteristics. Due to this, there are no overlapping securities between the pure growth and pure value indices. The concentrated exposures of the S&P Pure Style Indices potentially present them as better candidates for market participants looking to have precise tools in their investment process.

These differences drive the long-term performance differential between the two sets of indices, giving rise to distinct risk/return profiles. We report the risk/return differences between the style and pure style indices in Exhibits 2 and 3. For comparison purposes, we include the Russell Style indices, given that market participants also benchmark to those indices.

The pure style indices had higher average returns than the style indices; however, they also exhibited higher volatility, evidenced by the average annual volatility figures. The return/risk ratio shows that pure style displayed mixed performance results depending on the market-cap size, style orientation, and measurement period.

Both style and pure style indices use the same fundamental metrics to calculate style scores and to group securities into value and growth categories. Additionally, the pure style indices use style scores to determine constituent weights. Therefore, we expect the pure style indices to have stronger value or growth characteristics than their style peers. Exhibit 4 shows the annual averages of these ratios, which mostly line up with our expectations.

Across all size segments, the pure value indices historically had more attractive, or lower, price multiples than both the value indices and the underlying benchmarks. Interestingly, the pure growth indices tended to have lower valuation multiples than their traditional growth counterparts. A potential cause may be due to the higher sales and earnings growth rates of the pure growth indices versus the growth indices, outweighing the price difference.

For a deeper dive into the next generation of style indices, tune into our webinar at 2pm EST tomorrow: Sizing Up Your Style Strategies.

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

Looking at Sectors With a Style Lens

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Anu Ganti

U.S. Head of Index Investment Strategy

S&P Dow Jones Indices

We’ve previously observed that we can view the world through both a factor and a sector lens, but what about overlaying sectors and style? This is indeed possible, as sectors can serve as implementation vehicles to achieve a particular view on style.

Using value and growth scores that are reset annually for every constituent within the S&P Total Market Index, Exhibit 1 plots the 11 S&P 500® GICS® sectors on the value versus growth spectrum, calculated as an index-weighted average score at the sector level. The size of the bubbles is proportional to the market cap of the sectors. For example, Information Technology is the biggest bubble, as it has the largest index market cap among sectors (and it also has the lowest value score). Meanwhile, Financials, the third-largest sector by market cap, has the highest value score along with the second-highest growth score.

Investors looking to access value and growth can do so through sectors such as Energy and Financials (the far right side of Exhibit 1). Meanwhile, for those who seek to take a more singular growth bet, the new Communication Services sector is a natural option.

We can similarly apply a style lens across industries. Exhibit 2 shows that high value exposure is prevalent in Insurance and Metals & Mining, while we observe a greater growth tilt for Oil & Gas Exploration & Production and Healthcare Equipment.

Investors can achieve style exposures through sectors and industries, and it is useful to understand how these dimensions interact with each other.

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

Raising the Bar in Small Caps

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Chris Bennett

Former Director, Index Investment Strategy

S&P Dow Jones Indices

As a leading index provider with clients and customers around the world, S&P Dow Jones Indices regularly launches new indices.  Just like our children, we try to love them all equally.  Every now and then, however, a particularly exciting new index comes along.  Last week, our global equities group launched a potentially important new benchmark for global small cap investors, the S&P Global SmallCap Select Index Series.  This series is built on the basic principle that filtering out junk makes a big difference in small caps, and extends this concept globally.

Who needs earnings?  Contrary to the rumblings out of Silicon Valley, profitability is not a bad thing.  With small companies, earnings may be particularly important to long term returns, and trimming out poor performers can substantially improve investment performance in small cap portfolios.  For example, the S&P SmallCap 600®—which includes positive earnings criteria—has outperformed the broader Russell 2000 Index (with lower volatility) for more than 20 years.  This outperformance has been examined in some detail by earlier S&P DJI research, but this is the first time that S&P DJI has extended the concept in a consistent way to the global small-cap universe.

The S&P Global SmallCap Index (representing the portion of the S&P Global BMI made up from the smallest 15% of companies in each country by capitalization) provides the starting point for the “Select” series.  In order to become a member of the Select, companies must meet additional size and liquidity criteria, and must also post two consecutive years of positive earnings.  Around 5,000 of the 8,321 global small cap companies, accounting for around 4/5ths of the free-float market capitalization, were included in the Select index at the most recent rebalance.

The potential benefit of the methodology is demonstrated in the chart below, where we see consistent excess returns from the SmallCap Select series vs. its parents.  On a rolling five-year basis, for both the Global and Global Ex-U.S. versions of the small cap indices, the Select index outperformed most of the time, averaging around 1% per annum in excess returns.  A simple profitability screen, in other words, would have generated substantial excess returns relative to the unscreened small cap universe.

The series offers a global index as well as regional indices which can be further broken into country indices as needed.  Currently, the universe includes:

  1. S&P Global SmallCap Select Index
  2. S&P Global ex-U.S. SmallCap Select Index
  3. S&P Developed ex-U.S. SmallCap Select Index
  4. S&P Emerging SmallCap Select Index
  5. S&P/ASX Small Ordinaries Select Index

These indices could change the game for global small-cap investing and for benchmarking the performance of active small cap portfolios.  Those who take the time to look could discover a way to improve results in small caps.

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