Indexology^® Blog

We are excited to introduce a new index series utilizing sentiment—the S&P 500^® Twitter Sentiment Index Series, which adds another dimension to the way we measure broad U.S. equities.

Over the past few years, social media has evolved to encompass commentary about stocks and financial markets. As the technology has improved, these views are now able to be analyzed; as a result, it is possible to interpret and try to understand what the online community is saying about a specific company by aggregating an analysis of these messages. This index measures market sentiment using Twitter data, specifically Tweets containing $cashtags, which indicate that the Tweet is referring to a particular stock. S&P DJI uses artificial intelligence technology to analyze the sentiment around these stocks to generate a sentiment score for the companies within the S&P 500.

The S&P 500 Twitter Sentiment Indices have been created to reflect the performance of the companies in the S&P 500 that have the most positive sentiment, as indicated by the Twitter community. The index provides a means of examining whether the most positive sentiment names outperform their peers over a given period of time. Constant or building sentiment for the index members could lead to such outperformance, where changing sentiment might cause the opposite.

As of Nov. 18, 2021, the index series consists of the following indices:

S&P 500 Twitter Sentiment Index: This index is designed to track the performance of the 200 constituents with the most positive sentiment from the S&P 500, which are weighted on a float-adjusted market capitalization (FMC) basis, with a 10% cap at rebalance.

S&P 500 Twitter Sentiment Select Equal Weight Index: This index is designed to track the performance of a selection of the 50 constituents with the most positive sentiment from the S&P 500 Twitter Sentiment Index, which have been equally weighted at rebalance.

Both indices have been designed as diverse and liquid and actively filter for spam (lower-relevance Tweets), and each company included in the indices must have a sufficient number of Tweets to qualify.

Adding this exciting new dimension of analyzing and assessing sentiment in social media is just the start of this new chapter for S&P DJI. We are hoping to bring to market further factor-based, strategic indices capturing social media sentiment for the passive investment community, so stay tuned.

¹Back-tested information reflects the application of the index methodology and selection of index constituents in hindsight. No hypothetical record can completely account for the impact of financial risk in actual trading. For example, there are numerous factors related to the equities, fixed income, or commodities markets in general which cannot be, and have not been accounted for in the preparation of the index information set forth, all of which can affect actual performance. The back-test calculations are based on the same methodology that was in effect on the index launch date. However, when creating back-tested history for periods of market anomalies or other periods that do not reflect the general current market environment, index methodology rules may be relaxed to capture a large enough universe of securities to simulate the target market the index is designed to measure or strategy the index is designed to capture. The back-test for the S&P Twitter Sentiment Indices is calculated for the period January 2018 to October 2021. S&P Dow Jones Indices designed the sentiment scoring model using data from approximately the same time range. The sentiment scoring model is a natural language processing tool based on linguistic classification of the degree to which a Tweet is likely to be positive or negative. Complete index methodology details are available at www.spdji.com. Past performance of the Index is not an indication of future results. Prospective application of the methodology used to construct the Index may not result in performance commensurate with the back-test returns shown.

The S&P 500 Twitter Sentiment Index is a product of S&P Dow Jones Indices LLC. S&P^® and S&P 500^® are registered trademarks of Standard & Poor’s Financial Services LLC; Twitter^® is a registered trademark of Twitter, Inc. The Index is meant for informational purposes only and is not a recommendation to buy or sell any securities. Any investment entails a risk of loss. Please consult your financial advisor before investing.

S&P DJI has just released the final regional edition of our S&P Index Versus Active (SPIVA^®) Mid-Year 2021 Scorecards. The semiannual reports cover the performance of actively managed funds in the U.S., Canada, Latin America, Europe, South Africa, India, Japan, Australia, and our newest regional addition, the Middle East and North Africa (MENA). SPIVA Scorecards offer a wealth of insights into the performance of active funds globally, including the percentage of all the available actively managed funds that underperformed an appropriate S&P DJI benchmark over various time horizons. Exhibit 1 summarizes the performance of domestically focused active funds across the various regions over the one-year period ending in June 2021.

In every region apart from Australia, most active funds underperformed. Intriguingly, although we often hear that index-based strategies “don’t work” as well in Emerging Markets, the rate of underperformance  was generally higher in those markets: 86% of Indian active managers failed to beat the S&P BSE 100, with similar underperformance among Mexican and Brazilian funds. This speaks to the shrinking alpha that is often seen as markets increasingly professionalize; put simply, it becomes harder and harder to remain “above average.”

Beyond the headline figures, the biannual reports dig into a wide range of specialized equity and fixed income fund categories and, as usual, the latest reports identify a few pockets where active managers had more reason to boast, and those markets where outperformance was hardest to find. Exhibit 2 shows the top underperforming and outperforming fund categories across all our regional reports. Canadian Dividend & Income Equity funds had the largest rate of underperformance, with more than 98% of funds underperforming the S&P/TSX Canadian Dividend Aristocrats^®. At the other end of the spectrum, U.S. bond fund managers, in particular, stood out for their benchmark-beating returns (although the excellent 12-month record in the Government Long, U.S. Government/Credit Long, and Emerging Markets Debt fund categories is qualified by close to 100% underperformance over a 10-year horizon). The most extreme case of outperformance was among South African Short-Term Bond funds, with only 8% of active managers underperforming the STeFI Composite.

Turning to cross-region comparisons (summarized in Exhibit 3), the best active U.S. equity managers over the one-year period ending in June 2021 were, perhaps surprisingly, more likely to sit on a different continent than the stocks they managed, with 51% of Japanese and European active U.S. equity managers underperforming the S&P 500, versus the U.S.’s 58%. However, over the long run, U.S. active managers did achieve a better outperformance rate than other regional managers, not only in U.S. equities, but also across Global and Emerging Market equity market categories, too.

Explore the latest SPIVA scorecards at https://www.spglobal.com/spdji/en/research-insights/spiva/.

The saying goes, “What does not kill you makes you stronger,” but could that strength translate into a greater chance of survival? Perhaps, especially if all future risks were equal or sufficiently similar to the one that was survived—assuming, of course, that one learned from that first experience.

The survival of mutual funds could follow the same premise. Unfortunately, every day is different; economic, political, and public health circumstances constantly change, making each market observation an independent event.

The S&P Indices Versus Active (SPIVA^®) Latin America Scorecard compares the performance of actively managed mutual funds in Brazil, Chile, and Mexico to their benchmarks over 1-, 3-, 5-, and 10-year periods.

In the mid-year 2021 scorecard, we observed fund survivorship from December 2014 to June 2021 (14 semiannual reports) under all categories and horizons covered by the report.[1] In the case of the 10-year period, data is only available from December 2018 to June 2021 (six semiannual reports).

In Exhibit 1, we can see that the highest survival rates in all categories were in the one-year period, while the lowest survival rates were in the 10-year period—the longer the observation window, the lower the probability of survival.

It can also be observed that both the 1- and 10-year periods presented lower dispersion compared with the 3- and 5-year periods. The category with the highest dispersion in all observation periods was Brazil Corporate Bond Funds and the category with the lowest dispersion in all observation periods was Mexico Equity Funds.

To see the latest active versus passive results including the fund survivorship report, please see the SPIVA Latin America Mid-Year 2021 Scorecard.

[1] The categories covered in the SPIVA Latin America Scorecard are: Brazil Equity Funds, Brazil Large-Cap Funds, Brazil Mid-/Small-Cap Funds, Brazil Corporate Bond Funds, Brazil Government Bond Funds, Chile Equity Funds, and Mexico Equity Funds.

Research has shown that equally weighted indices have historically posted long-term outperformance¹ over their benchmarks—largely driven by their exposures to small size and value along with associated risk premia, in addition to a healthy dose of concentration reduction.² However, in accessing compensated factors and reducing concentration, the S&P 500^® Equal Weight Index could elicit some undesirable ESG consequences.

With many investors looking to integrate ESG considerations into their portfolios, is it possible to gain the benefits of equal weighting while incorporating ESG criteria? This question raises three sub-questions.

• Can ESG benefits be gained relative to the S&P 500 Equal Weight Index?
• Can factor exposures associated with equal weighting be gained within an ESG framework?
• Can we reduce concentration in a few names, while excluding companies that are undesirable from an ESG standpoint?

To give the game away early (in case you want to stop reading here): yes, yes, and yes.

Before addressing these questions, it helps to understand how the index is constructed (see Exhibit 1).

Based on this index construction, how does the S&P 500 Equal Weight ESG Leaders Select Index perform? We can see an excess return over the S&P 500 Equal Weight Index (see Exhibit 2), with comparable volatility, realizing an improved risk-adjusted return over each period examined historically (see Exhibit 3).

Can ESG benefits be gained? There were large improvements in both the S&P DJI ESG Score and carbon intensity¹ at the index level, with the S&P 500 Equal Weight ESG Leaders Select Index relative to the S&P 500 Equal Weight Index achieving a stronger ESG profile and lower carbon footprint (see Exhibit 4).

Can factor exposures be maintained?  The only significantly difference in exposure we can see is small size, as the S&P 500 Equal Weight ESG Leaders Select Index is not quite as exposed. But it still has more exposure to small size compared to the market-cap-weighted S&P 500 or S&P 500 ESG Index.

Can we reduce concentration within an ESG Framework? While there is more weight in the largest stocks in the ESG equally weighted index than in the S&P 500 Equal Weight Index, there is still a large concentration reduction from cap weighting—relative to either the S&P 500 or S&P 500 ESG Index.

Ultimately, if the factor exposures and concentration reduction of equally weighted indices with an improved ESG footprint sounds good, the S&P 500 Equal Weight ESG Leaders Select Index may be a good fit.

¹ Historical long-term outperformance was over market-cap-weighted indices.

² Rashid (2021) shows equally weighted indices have performed well during economic recovery. Bellucci & Gunzberg (2018) and Edwards, Lazzara, Preston & Pestalozzi (2018) highlight increased exposure of equal weighted indices to small size and value, while Ganti (2021) observes value exposures by equally weighted indices. Edwards, Lazzara, Preston, & Pestalozzi (2018) and Preston (2021) discuss benefits of concentration reduction.

³ We define carbon intensity as Scope 1 + Scope 2 + Scope 3 emissions/enterprise value including cash (EVIC

Explore how the design of the S&P 500 Factor Rotator Daily RC2 7% Index is helping democratize access to factor investing, providing a simple, rules-based blueprint for building dynamic factor strategies.