Indexology^® Blog

How does profitability influence risk and return in small-cap equities? S&P DJI’s Raghu Ramachandran and Garrett Glawe join Vanguard’s Ilene Kelman and Cardinal Investment Advisors’ Matt Padberg to take a closer look at aligning index objectives with strategic objectives.

2021 started on a hopeful note, with COVID-19 vaccines coming to save the world. However, as in many other parts of the world, Latin American countries struggled to control the pandemic’s impact on their economies and societies. Additionally, political uncertainty and civil unrest in several countries contributed to a disappointing year.

While most global markets experienced strong performance in 2021, the S&P Latin America BMI finished the year down 12%, with negative returns in three out of four quarters. It is interesting to note, however, that Latin America excluding Brazil had a different outcome, as the S&P MILA Pacific Alliance Composite gained 6.7% for the year (see Exhibit 1).

While headline indices from Argentina, Chile, Colombia, and Peru all closed 2021 in positive territory in local currencies, Mexico was the standout performer among Latin American countries as the S&P/BMV IRT gained 24.4% YTD (see Exhibit 2). The story was different in U.S. dollar terms, as all markets except for Argentina and Mexico ended in the red due to local currency depreciation against the U.S. dollar.

Brazil was the worst performer in 2021 in both Brazilian reals and U.S. dollars. Most Brazilian sectors underperformed; Financials, represented by the S&P Brazil BMI Financials Index (-24.3%), had significant losses and the greatest impact on the entire market. Mexico, on the other hand, had the largest annual gain since 2009, as shown by the S&P/BMV IRT. Most of this was driven by the double-digit gains of some of the largest Mexican companies like America Movil, Cemex, and Walmart de Mexico.

In terms of regional sectors, nearly all of them struggled to stay afloat (see Exhibit 3). In the end, for 2021, Communication Services (19.2% YTD), Consumer Staples (5.7% YTD), Energy (10.0% YTD), and Materials (3.1% YTD) were the only ones that accomplished that goal. The pandemic drove most people indoors to work, play, and shop. In Communication Services, companies like America Movil, Grupo Televisa, and Telefonica Brasil greatly benefited from increased subscribers to their online and pay TV services. Energy was driven up by solid annual price performances from Petrobras and Ecopetrol, which represented nearly 77% of the Energy sector. Consumer Staples, typically a reliable defensive sector, did not disappoint. Finally, Materials companies, which include producers of building materials, benefited from high demand for their products. Likewise, mining companies, particularly copper exporters, gained from historically high prices for their exports in 2021.¹ On the downside, Financials, the largest sector in the region, was down 21.6% for the year. Brazilian financial institutions, representing 64% of the sector, had the most losses for the year, greatly contributing to the region’s disappointing returns.

As the COVID-19 pandemic continues to evolve, uncertainty envelops the region at the start of 2022. High inflation, weakness in local labor markets, expectations for rising interest rates, and political instability in several Latin American countries continue to weigh on equity market sentiment. All this points to what could be a significant shift in economic and governmental policies in 2022. For better or for worse, it promises to be another fascinating year.

For more information on how Latin American benchmarks performed in Q4 2021, read our latest Latin America Scorecard.

¹ Source: S&P Global Ratings and CapitalIQ. Copper (Comex HG).

Equity markets have changed considerably over the past 10 years, reflecting the growth of stocks and sectors in each market. While this growth has led to increased concentration in most of the world’s largest equity markets, Australia is a notable exception, as diversification has improved both in terms of stock concentration and along sector lines.

We can analyze stock concentration at a high level by using the Herfindahl-Hirschman Index (HHI). This index is a widely used measure of market concentration that can also be applied to stock market indices. It is calculated by squaring the market share (weight) of each stock in an index and then summing the resulting numbers. A greater HHI indicates a higher level of market concentration, while a lower value indicates less concentration.

Exhibit 1 shows that market concentration declined significantly for the S&P/ASX 200 over the past decade, while it increased in benchmarks measuring four of the world’s five largest equity markets. The S&P 500 and Canada’s S&P/TSX Composite experienced the largest increases, while the U.K. was the only top five market to see a decrease.

Examining the S&P/ASX 200 and S&P 500, we can see how the sector dynamic played out during this period. The weight of Materials and Financials declined for both indices, while Information Technology increased. However, the Information Technology sector had barely any participation in the S&P/ASX 200 10 years ago, which perhaps makes this change even more significant in Australia, given the small initial base.

In Exhibit 3, we can see how much each sector’s weight has changed over the past 10 years. While some sectors declined across all markets, such as Energy and Materials, others like Information Technology have increased—this was most notable in the U.S., with its share in the S&P 500 going up by 13%.

For the S&P/ASX 200, Materials and Financials each declined 6%, while Health Care and Information Technology increased by 7% and 4%, respectively. This is quite notable, as the sectors that have traditionally dominated the index (Financials, Materials, and Energy) accounted for 67% of the index 10 years ago, and now with the growth of Health Care, Real Estate, and Information Technology, this has lowered to 53%.

In conclusion, changes in the level of diversification varied across markets over the past decade. While the S&P/ASX 200 has become more diversified as a result of growth within newly emerging companies and sectors, growth in other markets was centered on previously large companies and sectors, which led to more concentration in the market overall.

Global equities gained in the last quarter of the year, climbing 5.8% as measured by the S&P Global BMI. Shariah-compliant benchmarks, including the S&P Global BMI Shariah and Dow Jones Islamic Market (DJIM) World Index, outperformed their conventional counterparts by approximately 2.5% in the quarter due largely to their overweight in the U.S. Information Technology sector, which gained nearly 14% during Q4. Global Islamic indices finished the year with a near 2% advantage, while the performance differential varied across regions, as Asia Pacific developed and emerging markets underperformed their conventional benchmarks.

Drivers of 2021 Shariah Index Performance

While global equities enjoyed broad gains throughout 2021, the greatest contributors of Shariah index performance were at the sector and country level (see Exhibits 2 and 3).

Energy—which enjoyed a substantial rebound in 2021 after poor performance in 2020—was the best-performing sector. Due to its low weight in indices, however, performance impact was muted. Meanwhile, Information Technology—which tends to hold an overweight position in global Islamic indices—gained nearly 30%, contributing one-half of annual gains.

On a regional basis, high average weight toward the U.S. favored the S&P Global BMI Shariah during 2021, as the country enjoyed the best regional performance. The underperformance of the Asia Pacific developed and emerging markets regions limited overall gains, as Shariah-compliant stocks in Japan, South Korea, and China suffered during the period.

MENA Equities Continued to Gain in 2021

MENA regional equities gained considerably in 2021, as the S&P Pan Arab Composite advanced 32.7%. All MENA country indices finished the year in positive territory, led by the S&P United Arab Emirates BMI, which gained an impressive 50.8%, followed by the S&P Saudi Arabia BMI, up 34.8%. The S&P Egypt BMI led performance during Q4, rallying 16.3% and sending the country index into positive territory at year end.

For more information on how Shariah-compliant benchmarks performed in Q4 2021, read our latest Shariah Scorecard.

This article was first published in IFN Volume 19 Issue 02 dated the 12th January 2022.

We previously introduced the S&P 500 Twitter Sentiment Indices and analyzed their performance characteristics. We noted how the indices seek to capture the Tweet-based sentiment premium, with their differentiated performance being driven by differences in index construction and sector weighting. In this blog, we will examine their exposure to standard risk factors and analyze their correlation to other factor indices.

Significant Exposure to the Growth and Quality Factors

We start with a returns-based regression using the five-factor Fama-French model, including momentum as a sixth factor. Exhibit 1 displays the factor loadings, while the complete output of the regression model is shown in Exhibit 2.

Here are some of the key observations.

• A significant negative loading on the value factor indicates that the S&P 500 Twitter Sentiment Indices have had a growth bias.
• Both indices have had a positive loading on quality factors (profitability and investment), well in excess of the benchmark.
• Both indices have exhibited weak and insignificant exposure to the momentum factor, possibly due to the mean reversion that follows highly abnormal social media sentiment.
• For the S&P 500 Twitter Sentiment Select Equal Weight (EW) Index, exposure to small size has been in line with other equal-weight indices.

Variation in Exposure to Momentum and Volatility

Next, we evaluate factor exposures using a holdings-based approach. Following S&P DJI factor definitions, we calculate standardized z-scores for S&P 500 constituents on a monthly basis. Then, we use the constituent weights to evaluate the factor exposure for each index (and the benchmark). As expected, the S&P 500 Twitter Sentiment Select EW Index had the strongest exposure to the sentiment factor (see Exhibit 3). For the remaining factors, the broader S&P 500 Twitter Sentiment Index had a relatively stronger exposure.

Over time, different factors have exhibited different levels of variation in their active exposures (see Exhibit 4). Quality and value exposures appear relatively stable, while momentum and low volatility exposures show a fair amount of variation relative to the benchmark. The active exposure to momentum, in particular, seems to alternate between strongly positive and near zero, supporting the insignificant factor loading seen from the regression analysis (see Exhibit 2).

Active Return Correlations

To round out the characterization of the S&P 500 Twitter Sentiment Indices, we evaluate the correlation between their active returns (relative to the S&P 500) and those of the S&P 500 Factor Indices.

We see that both indices have exhibited low or negative active return correlation to many well-known factors (see Exhibit 5), pointing to potential diversification benefits when targeting multi-factor exposure.

¹ Back-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.

S&P® and S&P 500® are registered trademarks of Standard & Poor’s Financial Services LLC. Twitter® is a registered trademark of Twitter, Inc. These marks have been licensed for use by S&P Dow Jones Indices for use with the S&P Twitter Sentiment Index Series. The Indices are meant for informational purposes only and are not recommendations to buy or sell any securities. Any investment entails a risk of loss. Please consult your financial advisor before investing.