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Paint by Numbers: SPIVA Latin America Year-End 2021

Style Perspectives In Vogue

An ESG Solution for Varying Objectives: S&P 500 ESG-Based Indices

Tokens, Tokenized Funds, and the Evolution of Financial Markets

No Easy Answer: Sector and Factor Responses to U.S. Rate Hikes

Paint by Numbers: SPIVA Latin America Year-End 2021

Contributor Image
Sherifa Issifu

Senior Analyst, U.S. Equity Indices

S&P Dow Jones Indices

The S&P Indices Versus Active (SPIVA®) Scorecard1 provides a rich tapestry of data and insights on the active versus passive debate by comparing the performance of actively managed funds to their corresponding passive benchmarks. The SPIVA Latin America Scorecard is one of several regionally focused reports and covers the performance of active funds in Brazil, Mexico, and Chile. Below are some takeaways from our latest year-end 2021 report.

  1. It Is Difficult to Outperform the Benchmark over the Long Run.

In the short run, most Brazilian Government Bond Funds outperformed the benchmark, but this swiftly turned into underperformance for holding periods of three years or more. Brazilian Large-Cap Equity Funds fared better, as slightly more than half of actively managed funds outperformed the S&P Brazil LargeCap for up to five years. In the short run, it is not unusual to see the average active manager flipping between underperformance and outperformance. After a decade, however, at least 70% of active funds underperformed in each category; underperformance among Chile’s active equity funds was the highest, with 98% of funds lagging their benchmark over the past 10 years.

  1. Funds Struggle to Survive across Categories.

The price of being a poor-performing active fund is hefty, with the worst-performing funds liquidating or merging with other funds. Exhibit 2 shows that Brazil Corporate Funds had the lowest survival rate, with only 32% of funds still alive after 10 years. Interestingly, despite low rates of outperformance among Mexican equity funds, 78% managed to keep their doors open after a decade.

  1. Even Among Survivors, Outperformance Rates Are Poor.

Using Exhibits 1 and 2, we can divide the SPIVA database into three groups: funds that did not survive, funds that survived but underperformed, and funds that both survived and outperformed. We can see that even among the funds that survived, more than two-thirds underperformed in nearly every fund category.

  1. The Picture Doesn’t Improve Much on an Asset-Weighted Basis

Exhibit 1 shows the outperformance rate of funds on an equal-weighted basis. Some may make the argument that funds with larger assets have more assets because they have historically outperformed, and that they maintain relatively large assets because they produce “alpha.” Report 4 of our recent SPIVA Latin America Scorecard shows that in only one out of seven active fund categories were funds able to provide an average asset-weighted return above its appropriate benchmark over a 10-year period. Brazil Large-Cap Funds provided the one “success” story, but only narrowly.

  1. And Finally, There Is a Wide Range of Performance among Active Funds.

While “alpha” may exist, identifying outperforming managers is difficult and the performance distribution of actively managed funds is skewed. The interquartile range, which is the spread between the first and third quartile breakpoints of active funds in their respective category, is quite wide, showing there is a large difference between top and bottom fund performances.

Get the latest numbers and more from the SPIVA Latin America Scorecard here.

1 SPIVA Scorecards: An Overview. https://www.spglobal.com/spdji/en/education/article/spiva-scorecards-an-overview

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

Style Perspectives In Vogue

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Hamish Preston

Director, U.S. Equity Indices

S&P Dow Jones Indices

U.S. equities have had a tough start to the year amid rising inflation concerns, anticipated rate hikes by the Federal Reserve, earnings misses from several mega-cap companies, and ongoing geopolitical tensions emanating from the Russia-Ukraine conflict. Exhibit 1 shows that the S&P 500®, S&P MidCap 400®, and S&P SmallCap 600® all declined in the first two months of 2022, as did the majority of their respective sector, style, and pure style indices. Energy was a notable outlier, boosted by surging commodity prices.

While recent news flow had a similar directional impact on U.S. equities, the magnitude of impacts varied across sector and style segments. For example, Exhibit 2 shows that a whopping 41% separated the best-performing S&P 500 sector (Energy, up 28%) and the worst-performing sector (Real Estate, down 13%) in the first two months of 2022, while the S&P 500 Value (-3%) beat the S&P 500 Growth (-12%) by 9%. Such differences suggest that sector and style perspectives could have been helpful to navigate the recent market environment; avoiding the worst-performing segments or identifying the outperformers could have offered sizeable performance improvement.

Comparing dispersion figures for S&P 500 stocks, sectors, and styles offers a more formal way to assess the potential opportunity for outperformance (or embarrassment) from picking S&P 500 segments. Exhibit 3 shows that, on average, annualized monthly stock level dispersion (24%) was typically higher than sector dispersion (11%), which in turn was greater than style dispersion (3%).

In other words, about half the potential value of stock picking came from picking sectors, with about 14% of the potential value of selecting stocks coming from style selection. This is unsurprising, given that the S&P 500 comprises 505 stocks and 11 GICS sectors, but only two styles. Notably, though, style and sector dispersion figures have been similar in the first two months of 2022, averaging 8% and 13%, respectively: the potential value of style insights was similar to sector insights in recent months.

The potential value of style perspectives is even more pronounced after adjusting for capacity, since both the potential opportunity for outperformance (measured by dispersion) and the potential size of active positions (measured by the average constituent size) are relevant when comparing the value of insights into different segments. This is especially the case given the proclivity for smaller market segments to exhibit higher dispersion.

Exhibit 4 shows the average capacity-adjusted dispersion figures for S&P 500 style and S&P 500 sectors relative to S&P 500 stocks. Over the entire period, driven by the relative size of their respective components, insights into style were eight times more valuable than those for stocks, with sector insights being six times more valuable than for stocks. More recently, elevated style dispersion at the start of 2022 meant style insights could have been more than twice as valuable as sector insights at the start of the year, and over 10 times as valuable as stock insights.  

Hence, while it can sometimes be useful to do nothing, the recent divergence in style performance means some may find it useful to express views through a style perspective.

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

An ESG Solution for Varying Objectives: S&P 500 ESG-Based Indices

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Barbara Velado

Senior Analyst, Research & Design, ESG Indices

S&P Dow Jones Indices

When it comes to ESG indices, different objectives require different solutions. Indices can range from simple to sophisticated, concentrated to benchmark-like, broad environmental, social and governance to climate-focused, and more. Our growing suite of ESG indices aims to serve a wide range of ESG needs and support the alignment of investments with ESG principles.

When assessing ESG indices, users may have two questions.

  1. What is the investment objective in terms of:
    1. ESG benefits; and
    2. Active risk?
  2. Given the objective, which approach is more suitable:
    1. Simple; or
    2. Sophisticated?

Here, we focus on these questions by highlighting the outcomes achieved by S&P 500® ESG Indices.

ESG Benefits and Active Risk

ESG benefits and active risk are two important factors to be considered within any ESG index strategy. There is generally a trade-off between the ESG benefits achieved by the index and its active risk relative to the benchmark; hence, the two aspects should be looked at collectively. When viewing ESG enhancements through an active risk lens, we can assess how much improvement in S&P DJI ESG Scores the index achieves per unit of tracking error.1 Exhibit 1 shows S&P DJI ESG Score improvement against three-year tracking error, with the bubble size representing carbon intensity reduction.2

If the objective is to achieve high ESG score improvement per unit of tracking error, the S&P 500 ESG Tilted Indices (with various tilting levels) were efficient in meeting this goal. Within the various ESG series, the high-conviction S&P 500 ESG Elite Index led the way for S&P DJI ESG Score improvement, realizing similar carbon intensity reduction to its S&P 500 ESG Leaders Index counterpart, albeit with a higher tracking error. The flagship S&P 500 ESG Index stood firmly as the sustainable, benchmark-like option, with relatively low tracking error. Likewise, if carbon intensity reduction is required, the S&P PACT™ Indices (Paris-Aligned and Climate Transition Indices) achieved that most efficiently, while aligning with the Paris Agreement goals.

Performance

How have all the S&P 500 ESG Indices performed? The S&P PACT Indices are among the notable outperformers (see Exhibit 2).

Level of Sophistication

We saw how different ESG indices have reached specific ESG outcomes. But which approaches could be used to achieve those objectives? Exhibit 3 shows the spectrum of sophistication of S&P ESG Indices.

Simpler exclusions-based indices, such as the S&P Sustainability Screened and S&P Fossil Fuel Free Indices, remove companies involved in specific business activities. Going one step further, some strategies combine exclusions with a single ESG or climate objective, such as increasing exposure to best ESG performers (S&P ESG and S&P ESG Tilted Indices) or to low-carbon emitters (S&P Carbon Efficient Indices). When multiple ESG and climate considerations are required, a sophisticated approach like the S&P PACT Indices might be more appropriate.

Our growing suite of S&P ESG Indices could help provide clients with the necessary tools to navigate the diverse and evolving nature of ESG needs. When assessing ESG indices, it’s essential to consider the required investment and ESG objectives. Again, there’s an ESG solution for every need.

 

1 Tracking error is calculated as the standard deviation of monthly excess returns of the ESG strategy relative to the benchmark.

2 Carbon intensity is calculated using operational and first-tier supply chain GHG emissions, please see here for more information.

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

Tokens, Tokenized Funds, and the Evolution of Financial Markets

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Sharon Liebowitz

Senior Director, Innovation & Strategy

S&P Dow Jones Indices

When people ask me about cryptocurrencies, or digital assets more broadly, they generally ask about what’s in the news. Sometimes, it’s about a popular meme coin (e.g., Doge); other times, it’s about non-fungible tokens (NFTs) and the digital artworks that are seeing surprising prices; and still other times, it’s about the new corporate structure created in the form of a decentralized autonomous organization (DAO). It’s an exciting time for digital assets. Blockchain technology—with its security, immutability, transparency, and new way to transfer value—has spurred game-changing innovation.

What many people are less focused on, however, is how blockchain technology has also spurred innovation within the financial markets. Blockchain is leading the transformation from traditional markets to digital markets. This includes the creation of new entirely digital exchanges and the digitized assets, or tokens, that trade on them.

What is a token? A token is an asset that exists in digital form on the blockchain. It is issued on the blockchain and is a digital representation of ownership of an asset. This represented asset could be a traditional financial asset (e.g., stock, bond, gold, or real estate) or it could be a digital asset (e.g., cryptocurrency). Taking this a step further, a token can represent multiple assets in a single unit.

Interestingly, tokens are being used to represent a fund. As a tokenized fund, the token can represent all the constituents in an index in one token, similar to the way an exchange-traded fund (ETF) contains all index constituents as a single security.

The new tokenized funds bring several attributes. From a trading perspective, tokens tend to offer instant settlement, reduced counterparty risk, 24/7 trading, fractional shares, immutability, and auditability. From a market perspective, tokens may also offer global accessibility and reach new investors—including new target markets (e.g., crypto-first traders looking for an off-ramp to equity and new populations where traditional exchanges are less efficient or do not exist).

In addition, because tokens are programmable, fund operations can potentially be automated. This programmability uses smart contracts—essentially code embedded within the token itself that self-executes. Compliance features such as Know Your Customer (KYC) and Anti Money Laundering (AML), along with operational features like dividend payouts and proxy voting, can all be automated. These increases in efficiency may lead to a reduced cost structure over time.

Because they are securities, tokenized funds often trade on digital exchanges that are regulated. This has created a growth spurt in digital exchanges.

This can be seen by looking at the number of recently launched digital exchanges and products—there are a lot. For example, the SIX Digital Exchange (SDX), part of the SIX Swiss Exchange, went live in November 2021 with the issue of a tokenized bond.1 In Germany, the Boerse Stuttgart Digital Exchange (BSDEX), launched in June 2021, uses blockchain technology to trade cryptocurrencies and plans to start trading tokenized assets this year.2 In the U.S. in December 2021, a digital exchange launched the first tokenized funds tracking S&P DJI indices. And in January 2022, the U.S. SEC gave approval for the establishment of the Boston Security Token Exchange (BSTX), the first national blockchain-enabled securities exchange.3 Accenture, in a report published in June 2021,4 expects to see all exchanges fully digital by 2025.

At S&P DJI, we are excited to see our indices becoming digitized—in the format of a tokenized fund—as part of the evolution to digital markets. Currently, the digital market infrastructure stands alongside existing exchanges and asset structures. While we may debate the exact timeframe of this transformation, we are still in the early days of tokenization and digitization. We should expect to see the markets continue the move toward digital—with new regulations and additional products and exchanges transforming the financial markets as we know them.

Stay tuned to see how this journey continues!

 

1 https://www.coindesk.com/business/2021/11/18/switzerlands-six-digital-exchange-launches-with-blockchain-bond/

2 https://blackmanta.capital/first-digital-exchange-in-germany/

3 https://www.coindesk.com/business/2021/11/18/switzerlands-six-digital-exchange-launches-with-blockchain-bond/

4 https://blackmanta.capital/first-digital-exchange-in-germany/

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

No Easy Answer: Sector and Factor Responses to U.S. Rate Hikes

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Benedek Vörös

Director, Index Investment Strategy

S&P Dow Jones Indices

Although higher rates are generally seen as negative for risk assets, the initial stages of a monetary tightening cycle have not been disastrous for the U.S. stock market historically. However, while the overall market may muddle through just fine, the same may not be true for the different sectors and factors that compose a broad benchmark like the S&P 500®.

The stretch of history for which we have full data on the S&P 500’s various GICS® sectors and factor indices is around three decades long. However, the rate cycle moves slowly, with only four occasions of “liftoff” since 1994. We are presented not so much with a sample as a series of case studies. Nonetheless, history suggests a few top-level conclusions that sector- and factor-based equity investors might draw.

Turning first to sectors, Exhibit 1 shows the average excess returns of S&P 500 sectors in years when a rate hike cycle started and in other years.

Exhibit 1 suggests three distinct clusters of sectors based on their historical reaction to rate hikes.

  1. “Rate hike agnostics” – The performances of Energy, Industrials, Materials, and Consumer Discretionary were similar in years of first hikes and other years.
  2. “Rate hike underperformers” – Consumer Staples, Health Care, Financials, and Utilities underperformed the S&P 500 in the years when the Fed started raising rates. Utilities was the worst performing, confirming the sector’s “bond proxy” characteristics. Financials, which by convention is assumed to benefit from higher rates, also underperformed on average, but a look at the data reveals a major idiosyncratic event: in 1999, the S&P 500 was pulled up by Information Technology, and out-of-fashion Financials underperformed the index by 17%.
  3. “Rate hike beneficiaries” – This cohort contains Real Estate (established as a separate sector in 2016, therefore experiencing just two rate hike cycles) and Information Technology. Like Financials, Information Technology’s excess returns were greatly influenced by the 1999 dot-com bubble, during which year it outperformed the S&P 500 by 58%. If we take out 1999, the sector’s average excess return drops to just 5% in the other three calendar years when a rate hike cycle commenced.

Turning to factors, Exhibit 2 shows the average excess returns of S&P 500 factors in years when a rate hike cycle started and in other years.

In the case of factors, the “rate hike agnostic” group appears to be lacking in representatives, so we divide it into just two cohorts.

  • “Rate hike winners” – This group contains Momentum, High Beta, and Growth. All three factors’ gains can be ascribed to 1999, when they had a large tilt toward Information Technology and consequently outperformed the benchmark by 27%, 32%, and 7%, respectively. If we remove 1999 from the sample, the average excess return in the year of a first rate hike drops to 1.1%, -5.8%, and 0.5% for Momentum, High Beta, and Growth, respectively.
  • “Rate hike underperformers” – Just as for “winners,” 1999 greatly influenced this group’s excess returns. The three factors that lagged the most on average, Low Volatility, Dividend Aristocrats®, and Quality, underperformed the S&P 500 by 29%, 26%, and 14%, respectively, in 1999. Excluding 1999, both Low Volatility and Dividend Aristocrats would have outperformed the S&P 500 in the three other years in which a rate hike cycle started (by 2% and 1%, respectively), while Quality would have matched the return of the benchmark.

The overall takeaway from our analysis is that for both sectors and factors, the fact of a rate hike often played second fiddle to exogenous forces, such as a speculative bubble in dot-com stocks. While the Federal Open Market Committee’s activities are no doubt of importance to the relative returns of factors and sectors, an excessive focus on monetary policy at the expense of the broader economic and market environment could lead market participants astray when appraising prospects for the year ahead.

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